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MIMET Technical Bulletin | Volume 2 (2) 2011

EDITORIALEDITORIAL

CHIEF EDITOR

Prof. Dato’ Dr. Mohd Mansor Salleh

EXECUTIVE EDITOR

Dr. Mohd Yuzri Mohd Yusop

COORDINATING EDITOR

Pn. Nurshahnawal Yaacob

EDITOR

En. Aminuddin Md Arof

En. Ahmad Azmeer Roslee

En. Iwan Zamil Mustaffa Kamal

En. Hamdan Nuruddin

En. Aziz Abdullah

En. Redzuan Zoolfakar

Dr. Siti Habibah Shafiai

Pn. Nik Harnida Suhainai

EDITORIAL MEMBERS

En. Kamarul Nasser Mokri

Pn. Marhaini Jamaluddin

Pn. Norfadhlina Khalid

Pn. Maziah Mohd Ali

En. Rohaizad Hafidz Rozali

En. Azzahari Hamid

En. Mohd Khairuddin Abdul Karim

CHIEF’S EDITOR MESSAGE

THE EFFECTIVENESS OF CAD

TRAINING AMONG LOW AND HIGH

SPATIAL VISUALIZATION

Page 1-12

FRACTAL DIMENSION Page 13-21

APPLICATIONS OF IMO STABILITY CRITERIONS TO DETERMINE THE OPERATIONAL LIMIT OF A BARGE

Page 22-31

ENHANCEMENT OF UNDERWATER IMAGES

Page 32-44

OPTIMIZATION OF QUALITY

IMPLEMENTATION IN

SHIPBUILDING, SHIP REPAIRING

AND OFFSHORE CONSTRUCTION IN

MALAYSIA TOWARDS GREATER

COMPETITIVENESS

Page 45-56

PERFORMANCE ANALYSIS OF

WIDEBAND STACKED MICROSTRIP

ANTENNA FOR WIMAX

APPLICATION

Page 57-66

AN ANALYSIS ON THE PLURAL

INFLECTIONS OF ENGLISH LANGUAGE AMONG MALAY

STUDENTS

Page 67-76

STUDY ON HIGH ENERGY EVENT INDUCED BY BOATS AT SEPETANG

RIVER

Page 77-82

HOMOTOPY PERTURBATION

METHOD AND HOMOTOPY

ANALYSIS METHOD IN SOLVING

ORDINARY DIFFERENTIAL

Page 83-98

PETROLEUM TECHNOLOGY:

A BRIEF TECHNICAL REVIEW

Page 99-106

EFFECT ON SURFACE MORPHOLOGY OF PLASTICIZED POLY (ETHYLENE

OXIDE) BASED POLYMER ELECTROLYTES

Page 107-114


© 2011 Marine Frontier @ UniKL MIMET Technical Bulletin. This publication is copyright under Malaysian Institute of Marine Engi-

neering Technology Universiti Kuala Lumpur.

All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system or transmitted without the prior permission of the copy-

right owner. Permission is not, however, required to copy abstracts of papers or of articles on condition that a full reference to the

source is shown.

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ISSN 2180-4907

mailto:[email protected]

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Research in Marine Engineering

Being one of the very few institutions of higher learning specializing in marine and maritime engineering, UniKL MIMET has to

prepare itself to contribute new knowledge through research and development activities. MIMET has 80 academic staff with varied

specialist backgrounds covering the whole field of ship design, naval architecture, propulsion systems, materials, ship construction

and many others. However, it must be realized that MIMET’s academics will not be able to cover such a wide area of R&D. Hence,

there must be a proper selection of areas of research focus dependent on availability of expertise and manpower, equipment and

industrial requirements. With collaboration with other Universities, technical research institutions and industries, the coverage of

research areas will be much widened.

Some possible research thrusts would be the following:

1. Design, development and manufacture of propellers, using new materials and production techniques to ensure longer life and

more efficient performance.

2. The production and use of cheaper new composite materials for the local fishing boat industry.

This area of development will also contribute to the greening and environmental sustainability owing to the use of natural

products plentifully available within the country. MIMET’s research group on composite materials for boats has started work. The

relevant properties of these new materials for use in the marine environment must be investigated and techniques found to improve

these if found to be wanting.

3. New designs for local fishing boats.

This is an area ripe for research in order to improve the lot of our fisherman by bringing new technologies to them. These

redesigned vessels, are based more on modern materials instead of the traditional wooden boats. Going further, the boats stability

and propulsion systems need to be examined as well in order to be economical.

4. Non-technical research areas.

MIMET also run the Bachelor of Maritime Operations programme, specializing in producing graduates to venture into

employment areas of shipping management, seaport operations, shipyard administration and other maritime auxiliary services.

Research of the applied variety need to be carried out in order to improve the management, administration and law enforcement

activities. With this information, improvements in the shipbuilding, ship repair industry’s performance can also be better

coordinated.

There a lot more new areas for research in the marine engineering and maritime sectors in our country. The above four main areas

are only examples. Let us hope that our academics in all our Universities can start to do the research and collaborate with industries

as well.

Chief Editor.

MIMET Technical Bulletin

Volume 2 (2) 2011 1

THE EFFECTIVENESS OF CAD TRAINING AMONG LOW AND HIGH SPATIAL VISUALIZATION ABILITIES UNDERGRADUATES

AMINUDDIN MD AROF1, NURUL ASIMA ZAINON2, NURSYUHADA RAZALI3

1,2 Department of Marine and Design Technology 3 Bachelor of Maritime Operations Programme

Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur

Abstract

Researchers have identified that Spatial Visualization (SV) ability is an important factor in determining the success of indi‐viduals in many disciplines of studies and vocations. Hence, this paper would try to explore the importance of SV ability in CAD training and would identify whether CAD training could be utilized to enhance one’s SV ability after a certain period of time. Although earlier research findings conducted in different environments were inconclusive, it is arguably worth‐while for a similar study to be conducted in our local environment. For the purpose of this study, undergraduate students of UniKL MIMET who were enrolled into a CAD 3‐D course were divided into two separate groups of Low SV and High SV abilities. A similar training was given to all subjects and at the end of the training a post‐test was administered to deter‐mine whether the treatment provided was effective in enhancing their SV abilities. It is hoped that the findings of this pa‐per would be able to trigger further research in the development of a treatment program using CAD for the purpose of improving students’ SV ability.

Keywords: Computer Aided Design (CAD), Spatial Visualization (SV), Purdue Spatial Visualization Test: Rotations (PSVT:R)

Introduction Spatial visualization (SV) is a fundamental skill in engineering and technology fields. According to McGee (1979), it is a measure of the ability to mentally restructure, or manipulate the components of the visual stimulus, and involves recog‐nizing, retaining and recalling configuration when the figure or parts of the figure are moved. In technical and technology education, ranging from traditional board drawings of multi‐views, sections, and assemblies, to modern solid modelling using CAD software, almost all product designs require the visualization of 3‐D objects. Hence, SV ability has been argued by many researchers as an important component of psychometric ability that can assist students to successfully complete their technical and technology education. Computer‐aided design (CAD) involves the use of computer technology for the design of objects either real or virtual. Such technology may be used to design curves and figures in two‐dimensional (2‐D) space; or curves, surfaces or solids in three‐dimensional (3‐D) objects. CAD is an important industrial art extensively used in many applications, including ship‐building, automotive, aerospace, industrial and architectural design, animation and many more. Contemporary CAD soft‐ware packages range from 2‐D vector‐based drafting systems to 3‐D solid and surface models. 3‐D CAD drawings also al‐low computations of mass, volume and surface area in a matter of seconds.

___________________________________________

Corresponding author: [email protected]

Received: 18th September 2011, Revised: 4th October 2011, Accepted: 4th October 2011



Volume 2 (2) 2011 2

Purpose of the Study

The purpose of this study is to identify whether CAD training can be utilized to enhance undergraduates’ SV ability. It is also meant to identify whether individual differences in SV ability have some relevancy to CAD training. Numerous stud‐ies have argued that CAD training was not able to significantly enhance students’ SV abilities (Scribner & Anderson 2005; Sorby 1999; Braukmann & Pedras 1993). Nevertheless since those studies were done in different environments, it would be worthwhile for a similar research to be repeated in our local environment.

Computer‐Aided Design (CAD)

According to Mack (1992), CAD involves using computer hardware and software to manipulate visual stimuli on the computer screen and refers to any kind of activity that uses a computer to aid in the creation, modification, presentation and analysis of a design. Although the manipulation can also be conducted by using traditional drafting equipment, it was very difficult for someone who was not a trained drafter, engineer or architect to visualize how an object will look like after it was modified. With the advent of CAD technology, even a lay man can look at a computer generated image and get a better understanding of how the image would look if it were modified in some way.

CAD can be categorized into two types, 2‐D and 3‐D. While there are a variety of CAD software programs currently available, the most basic programs include some form of a 2‐D modelling. A 2‐D CAD is almost similar to drawing on a drafting board. It is essentially a flat view usually dimensioned and detailed to some types of standard. For instance, 2‐D drafting may be used in the creation of the floor plan of a house. Tasks typically associated with 2‐D drafting may involve curve creation, point construction, rotating, and scaling. On the other hand, 3‐D CAD software allows users to take their 2‐D creations to the next level. With most CAD software, 3‐D models can be easily converted into 2‐D drawings in order to be presented as traditional drafting documents. 3‐D drafting is generally considered a more realistic approach to drafting because it closely resembles real‐life objects. 3‐D modelling is used in the creation of solids, such as machine parts, bridges and buildings. Each 3‐D model is a replica of an existing object or idea of an object but in digital format which can be up‐scaled or down‐scaled or even modified to any specific tolerance. These digital objects are then ready for multiple views, or cross sections, dimensions and details, just like 2‐D drawings. Prior to the development of modern CAD programs, the development or modification of a physical model was very difficult and time consuming. Hence, the most effective way to convey the designer’s idea was through a drawing. Since a designer was limited to working in 2‐D, drafting rules were developed to represent details of 3‐D objects on paper by presenting three projected views. Due to the lengthy process, long lead times for manual drawing preparation were an accepted fact. The long lead time required for drafting has nevertheless, become history with the advent of CAD technol‐ogy that has evolved from a merely automated drafting facility to those that include the functions of three‐dimensional modelling and computer‐simulated operation of the model. The available CAD capability provides the benefit in shorten‐ing the lead time for drafting as one of its main advantages. It is much easier and faster for a draftsman to enter, modify and plot a drawing with CAD. Similarly, rather than having to build prototypes and change components to determine the effects of tolerance ranges, engineers can use CAD software to simulate operations to determine loads and stresses. The way the CAD operator processes information can be summarized as occurring in four steps: (a) attending to graphic stimuli and alphanumeric information which appears on the screen; (b) recognizing familiar patterns such as geo‐metrical shapes, and acquiring and integrating new information; (c) assessing the design with respect to the needed al‐terations and; (d) deciding on a response such as to maintain, change or modify the design (Mack 1992). Besides reducing the lead time required to complete the drafting process, CAD has also enabled draftsmen, designers and other interested individuals to process visual information faster. By having this advantage, the individual can decide on drawing modifica‐tions without having to modify the existing hard copy each time a change is made.


Volume 2 (2) 2011 3

Spatial Visualization Ability The concept of spatial ability has been a significant area of research in education psychology since the 1920s or 1930s (Sorby 1999). It has been considered as a component of human intelligence by cognitive psychologists for many years such as through the work of development pioneers such as Piaget, Thurstone, Thorndike and Lowenfeld (McGee 1979B; Piaget 2001; Hartman et. al 2006). Many definitions are often applied to the term spatial ability and it is often interchangeably used with descriptors such as visualization and spatial visualization. Other synonymously used terms are like spatial skills, spatial intelligence, spatial orientation (SO) and spatial visualization (SV) ability (Nolen 2003; Hartman et. al, 2006). Researchers that studied spatial ability also disagree on the key components or sub‐factors that constitute spatial ability. There are several approaches in classifying spatial ability that have been discussed in the preceding paragraphs. Nev‐ertheless, Werthessen (1999) concluded that out of all the approaches used, the two most common components to all definitions are the SV and SO abilities. Hence, for the purpose of this research, the researchers will adopt the classifica‐tion that divides spatial ability into SV and SO where focussed will be given to SV ability. Besides the definitions put for‐ward by McGee (1979A), there are other definitions of SV ability. Linn & Petersen (1985) for instance, describe SV as “commonly associated with those ability tasks that involve complicated, multistep manipulations of spatially presented information”. It may involve the processes required for spatial perception and mental rotations but are distinguished by the possibility of multiple solution strategies (Linn & Petersen 1985). If analysed further, one can see that the ability of mental rotation is a part of the SO ability in definitions put forward by Ekstrom et. al (1976) and McGee (1979A) but for Linn and Petersen, such ability may be a standalone ability and could be incorporated as part of the SV ability if it involves multiple steps solution.

Similarly Seng & Yeo (2000) argue that SV refers to “the subjects’ ability to do complex multistep processing of spatial information”. Strong & Smith (2001) in discussing the various definitions of spatial ability conclude that SV “is the ability to manipulate an object in an imaginary 3‐D space and create a representation of the object from a new viewpoint”. It requires serial operations such as rotation in a three dimensional space or unfolding of flat patterns. Hence, it can be ar‐gued that the requirement of serial operations is similar to multi steps process that would incorporate SO ability into SV ability. Due to the variety of approaches used to define SV, the researchers will adopt a flexible approach in the definition of SV ability. Other factors in spatial ability such as SO, mental rotation and spatial perception that may overlap with the operational definition of SV will be incorporated as part of the SV ability. Assessment of SV ability Many types of instrument have been identified for the assessment of SV ability. Among the most commonly used are the Purdue Spatial Visualization Test: Rotations (PSVT:R), Mental Rotation Test (MRT), Mental Cutting Test (MCT) and Dif‐ferential Aptitude Test: Space Relations (DAT:SR). Others include the Bennet, Seashore and Wesman Space Relations Test (BSWSRT), Water Level Test (WLT), Surface Development Test (SDT), Inventory of Piaget’s Development Tasks (IPDT) and Black and Black Figural Classification Test (FCT). The PSVT:R was devised to test a person’s ability to conceive what an object will look like from different perspectives. This testing instrument was used to identify weaknesses in SV ability and to assess the impact of experimental course (Sorby & Baartmans 2000). It consisted of 36 questions and is equally divided into 3 sections namely Developments, Rota‐tions and Views (Guay, 1976). Besides the original 30‐item PSVT:R test, Bodner & Guay (1997) has introduced a shorter 20‐item version by removing questions 6, 8, 11, 14, 20, 21, 22, 24, 26 and 30. The reliability of the 20‐item version has been tested by using Kuder‐Richardson 20 (KR‐20) and split‐half (SH) reliability coefficients, which suggest that the PSVT:R is internally consistent. (Bodner & Guay 1997) Due to its high consistency and reliability, the researchers have selected the 20‐item PSVT:R as an instrument for the pre‐test and post‐test. A sample problem from PSVT:R is shown in Figure 1.


Volume 2 (2) 2011 4

CAD Training at UniKL MIMET At University Kuala Lumpur, Malaysian Institute of Marine Engineering Technology (UniKL MIMET) CAD courses are offered to Diploma of Engineering Technology (DET) and Bachelor of Engineering Technology (BET) undergraduates. Com‐pared to the other programmes, undergraduates enrolled into the DET in Ship Design (DET SD) and BET in Naval Architec‐ture and Shipbuilding (BET NASB) are offered the most number of CAD courses. Among the courses offered are CAD 2‐D, CAD Modelling Concept, Computer Aided Ship Design (CASD), CAM 2‐D & 3D, and Electrical CAD. The university is licensed to utilized state‐of‐the‐art CAD software from renowned CAD developers for the instruction of its undergraduates. The available software are Auto‐CAD, Autodesk Inventor, MaxSurf, Ship Constructor and AlphaCAM.

For the purpose of our experiment, we have chosen DET SD undergraduate students enrolled in CAD Modelling Con‐cept (CAD‐MC) course. The students were in their fourth semester and have passed in their Manual Drafting and CAD 2‐D courses as pre‐requisites prior to their registration into the CAD‐MC course that emphasized on CAD 3‐D. The primary fo‐cus of this course is to study and develop three dimensional geometric computer models. Topics include learning to think in three dimensions, the creation of 3D objects, document assemblies using standard drawing views and creating anima‐tions of exploded views.

Figure 1: Sample Problem From PSVT:R (Source: Guay 1976)


Volume 2 (2) 2011 5

The principle objectives of this course are to develop the student’s basic knowledge, skill and proficiency with CAD software to create 3D geometric computer models. The student’s study and problem solving skills will be enhanced through assigned exercises, practical tests, a project and a practical exam. This assessment will be directed toward the development of independent thinking to resolve a variety of design problems using CAD software. At the end of the course, students will be able to identify the main user interface components that are common to CAD environment, and describe how to access different tools. They will also be familiar in utilizing the sketch tools to create 2‐D sketch geometry, and use geometric constraints to control sketch geometry. The undergraduates would also be able to create features us‐ing extrude, revolve and loft tools, and create swept shapes by sweeping a profile along a 2‐D or 3‐D path. Additionally, students would be able to use the hole and thread tools to place hole and thread features on part model, and create thin‐walled parts using the shell tool. This course will also teach undergraduates how to assemble the various parts and create animation. In this context, at the end of this course students will be able to place assembly constraints on components in the assembly, and use the Content Centre to place standard components into assembly design and create animations of exploded views in a presen‐tation file. Upon completion of this course, students should be able to follow drafting standards while dimensioning and annotating drawing views with centrelines symbols, leaders, hole and thread notes, hole tables, automated balloons, and part lists. Based on the above justification, the CAD‐MC course has been chosen for our pilot study since it can present a great challenge for undergraduate students to mobilise their SV potentials in order to succeed in the designated course. The Pilot Test A total of 40 students who were enrolled into the CAD‐MC course have volunteered to undergo the pilot test. The pre‐test was administered before the training commenced on January 13th, 2010. The training was conducted for 14 weeks with a four hour instruction per week. Upon completion of the training, a post‐test was administered between April 21st and April 23rd, after the undergraduates have completed their final assignments. The outcomes of the 20‐item PSVT:R tests are as follows:

Table 1: Outcomes of PSVT:R Tests


Volume 2 (2) 2011 6

In order to test for normality of data, the Tests of Normality from the Statistical Package for Social Sciences (SPSS) were utilized. The outcome of the tests is as follows:

a Lilliefors Significance Correction From the tests above, the Shapiro‐Wilks statistics has to be chosen since the experimental subjects are less than 50. Although the statistic range from 0.879 to 0.960, only the p‐value (significant) for the pre‐test is greater than the signifi‐cant level accepted in most social science research where alpha > 0.05. Hence, only the data for pre‐test do not violate the normality assumption. The p‐value for post‐test is lower than alpha, indicating that the assumption of normality is vio‐lated. Nevertheless, since the experiment involved more than 30 subjects, it has been generally argued that the subse‐quent result in testing the differences between mean and standard deviation using t‐Test will still provide correct conclu‐sions.

The results of the Paired Sample t‐Test are shown in the above tables. In the pre‐test the students scored 13.125 and in the post‐test they scored 15.2. The difference was statistically significant at alpha < 0.05 with the t‐value of ‐11.735. Hence, the test has shown that CAD training is effective in enhancing the SV ability among undergraduates.

Table 2: Tests of Normality

Table 3: Paired Samples Statistics

Table 4: Paired Samples Test


Volume 2 (2) 2011 7

The Experiment The experiment involved a combination of 60 students who have enrolled into the CAD MC course in January 2010 and January 2011 semesters. The reason for this combination was due to the insufficient number of students enrolled for this course in one semester. Other than the different in timing between the two groups, the other variables such as stu‐dents’ background (i.e. without prior exposure to 3‐D CAD training), type and duration of treatment and the trainer in‐volved were similar. The pre‐tests were administered before the trainings commenced on January 13th, 2010 and January 10th, 2011 respectively. The trainings were conducted for 14 weeks with a four hour instruction per week. Upon comple‐tion of the trainings, post‐tests were administered between April 21st to April 23rd, 2010 and April 18th to April 22nd, 2011 after the undergraduates have completed their final assignments. The outcomes of the 20‐item PSVT:R tests are as fol‐lows:

In order to test for normality of data, the Tests of Normality from the Statistical Package for Social Sciences (SPSS) were utilized. The outcome of the tests is as follows:

Table 5: PSVT:R Tests Overall Result

Table 6 : Tests of Normality


Volume 2 (2) 2011 8

From the tests in Table 6, the Kolmogorov‐Smirnov statistics can to be chosen since the experimental subjects are more than 50. The test statistics range from 0.118 to 0.204 and the p‐value (significant) for both the pre‐test and post‐test are below the significant level accepted in most social science research where alpha > 0.05. Hence, both data violate the normality assumption. Nevertheless, since the experiment involved more than 30 subjects, it has been generally argued that the subsequent result in testing the differences between mean and standard deviation using t‐Test will still provide correct conclusions.

The results of the Paired Sample t‐Test are shown in the above tables. In the pre‐test the students scored a mean of 13.7833 and in the post‐test they scored a mean of 15.2833. The difference was statistically significant at alpha < 0.05 with the t‐value of ‐2.569. Hence, the test has shown that CAD training is effective in enhancing the SV ability among un‐dergraduates. In order to further determine the effectiveness of CAD training, the students will be divided into two groups i.e. those with Low SV ability group and those with High SV ability group. In ensuring that the subjects are evenly divided those who scored 14 marks and below in the pre‐test were designated to the Low SV group whilst those with a score of 15 and above were assigned to be in the High SV ability group. With this division, every group will comprise of 30 subjects. The Relevance of SV Ability to CAD Training In determining the relevancy between SV ability and their performance in CAD training, students from both Low SV and High SV groups were given coursework comprising of 3 tasks (35%), 3 quizzes (15%) and a project (30%) throughout the 14 weeks including the final practical assessment (20%) in Week 14. The mean score for 30 subjects in the Low SV group is 66.7% whilst the mean score for the other 30 subjects in the High SV group is 71.9% as highlighted in Table 9 be‐low.



Table 9: One‐Sample Statistics.


Volume 2 (2) 2011 9

The comparison between the means using T‐Test showed that the difference was statistically significant at alpha < 0.05 with the t‐value of ‐2.660. From Table 9 above, it has been demonstrated that the performance of the High SV group is 5.2% better than those of the Low SV and is slightly above the significant level of 0.05 or 5% reflecting the correlation between SV ability and performance in CAD training. The Effect of CAD Training in Enhancing the SV among Low SV Students In order to determine the effect of CAD training in enhancing the SV among Low SV students, 30 subjects with a pre‐test score of 14 and below were grouped into this category. Before the 14‐week training commenced, a 20‐item PSVT:R test was administered to the students as a pre‐test. Similarly, the same 20‐item PSVT:R test was administered at the end of the treatment period as a post test instrument. The outcome of the 14‐week CAD training is as follows:





Volume 2 (2) 2011 10

As evidenced from Table 11, the mean of the post‐test at 13.80 is much higher than mean of the pre‐test of 10.37. By percentage there has been a 33.1% improvement in the performance of the Low SV students in the post‐test after receiv‐ing a 14‐week CAD training. Based on the Paired Sample Test result at Table 12, the differences between pre‐test result and the post‐test result was statistically significant at p = 0.05 with t value of ‐4.011. Hence, CAD training is an effective treatment to improve the SV ability of undergraduate students with Low SV ability The Effect of CAD Training in Enhancing the SV Among High SV Students In determining the effect of CAD training in enhancing the SV among High SV students, the other 30 subjects with a pre‐test score of 15 and above were grouped into this category. Before the 14‐week training commenced, a 20‐item PSVT:R test was administered to the students as a pre‐test. Similarly, the same 20‐item PSVT:R test was administered at the end of the treatment period as a post test instrument. The outcome of 14‐week CAD training is as follows: .

As evidenced from Table 13, the mean of the post‐test at 16.77 is slightly lower than the mean of the pre‐test of 17.20. By percentage, there has been a 2.5% reduction in the performance of the High SV students in the post‐test after receiving a 14‐week CAD training. Based on the Paired Sample Test result at Table 14, the differences between pre‐test result and the post‐test result was statistically not significant at p = 0.05 with t value of 0.688. Hence, CAD training is not an effective treatment to improve the SV ability of undergraduate students with High SV ability.




Volume 2 (2) 2011 11

Conclusion In retrospect, SV ability is an essential component of human intelligence required for one to succeed in many fields such as engineering and architecture. Many researchers have argued that such ability may be developed through various kinds of exposure and training that include manual drafting, real modelling, playing computer games and using specific computer applications. In determining whether CAD software can be utilised to enhance SV ability, earlier experiments that were generally conducted in developed countries have found that the treatments using CAD were not significantly effective. Nevertheless, from the experiment conducted involving 60 undergraduate students, it has been discovered that a 14‐week CAD 3‐D training has been able to significantly enhance the SV ability of undergraduate students undergoing the prescribed treatment. At the same time, this research was also able to determine the relevancy of SV ability and stu‐dents’ performance in CAD training, where students of higher SV group have performed significantly better than their peers of the lower SV group. It is hoped that, the preceding findings would provide us and other researchers the impetus to explore the prospect of using CAD‐3D in enhancing human SV ability in a more comprehensive manner. Acknowledgement The authors would like to thank Universiti Kuala Lumpur as the Short Term Research Grant (STRG) sponsor for this research work. References Bodner, George M, and Guay, Roland B. (1997) The Purdue Visualization of Rotations Test, The Chemical Educator, Vol 2, No 4, New York: Springer‐Verlag, 1‐17. Braukmann, J. and Pedras, M.J. (1993), A comparison of two methods of teaching visualization skills to college stu‐dents, Journal of Industrial Teacher Education, Vol 30 No 2, Virginia Tech: National Association of Industrial & Technical Teacher Educators, 65‐80. Ekstrom, R.B., French,J.W., Harman, H.H.and Dermen, D. (1976), Manual for kit of factor‐referenced cognitive tests, Educational Testing Service, New Jersey: Princeton. Guay, Roland (1976), Purdue Spatial Visualization Test, Purdue Research Foundation. Hartman, N.W., Connoly, P.E., Gilger, J.W., Bertoline, G.R.and Heisler, J. (2006), Virtual Reality‐based Spatial Skill As‐sessment and its Role in Computer Graphics Education, ACM SIGRAPH 2006 Educators Program SIGGRAPH ’06, ACM Press. Retrieved: 3 Sep 2008. Available at http://portal.acm.org.newdc. Linn, M.C. & Petersen, A.C., (1985), Emergence and Characterization of Sex Differences in Spatial Ability: A Meta‐Analysis, Child Development, 56, Ann Arbor: The Society for Research in Child Development, 1479‐98. Mack, Warren E. (1992), The Effect of Training in Computer‐Aided Design on the Spatial Visualization Ability in Se‐lected Gifted Adolescents, An unpublished dissertation for the degree of Doctor of Education in Vocational and Technical Education, Blackburg Virginia: Virginia Polytechnic Institute and State University. McGee, M.G. (1979A), Human Spatial Abilities, Sources of Sex Differences, New York: Praeger. McGee, M.G. (1979B), Human Spatial Abilities: Psychometric Studies and Environmental, Genetic, Hormonal, and Neurological Influences, Psychological Bulletin, Vol 86 No 5, Washington DC: American Psychological Association, 889‐918.

http://portal.acm.org.newdc


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Nollen, Jennifer, L. (2003), Multiple Intelligences in the Classroom, Education, 124,1, Ann Arbor: Proquest Education Journals, 115‐119. Piaget, Jean, (2001), The Psychology of Intelligence, (Translated by Piercy, M. and Berlyne, D.E.), NY & London: Routledge. Scribner, Shauna A. and Anderson, Marcia A (2005), Novice Drafters’ Spatial Visualization Development: Influence of Instructional Methods and Individual Learning Styles, Journal of Industrial Teacher Education, Vol 42, No 2, Virginia Tech: National Association of Industrial & Technical Teacher Educators, 38‐60. Seng, S. & Yeo, A., (2000), Spatial Visualisation Ability and Learning Style Preference of Low Achieving Students, Re‐search Report, EDRS. Sorby, Sheryl, A., (1999), Developing 3‐D Spatial Visualization Skills, Vol 63, No 2, Engineering Design Graphics Journal, Wasington DC:The American Society for Engineering Education, 21‐32. Sorby, S.A. and Baartmans, B.J. (2000), The Development and Assessment of a Course for Enhancing the 3‐D Spatial Visualization Skills of First Year Engineering Students, Journal of Engineering Education, 89,3, Ann Arbor: Proquest Educa‐tion Journals, 301‐7. Werthessen, Heather (1979), Instruction in Spatial Skills and its effect on Self‐Efficacy and Achievement in Mental Ro‐tation and Spatial Visualization, An unpublished dissertation submitted in partial fulfilment of the requirements for the degree of Doctor of Education, Teachers College, Columbia University.


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Abstract

Driver drowsiness is a major cause of severe accidents in transportation system. Electroencephalography (EEG) signal may be one of the most predictive and reliable drowsy indicators. This signal can be divided into four major frequency bands; beta wave, alpha wave, theta wave and delta wave. A fractal dimension (FD) analysis for extraction frequency band of EEG signal was performed and it was found that FD will increase when the frequency band increased. Results demonstrate that fractal dimension could be used as assisting parameter in computer assisted drowsiness detection. Keywords: Electroencephalography (EEG), fractal dimension, Higuchi’s Algorithm, Katz’s Algorithm

Introduction

Driver drowsiness has implications in road fatalities and is major hazard in transportation system. When drowsy, the decreased physiological arousal, slowed sensory motor functions and impaired information processing can diminish a driver’s ability to respond effectively to unusual or emergency situations. Presently, several studies have tried to model the behaviour of drowsy driver by establishing links between drowsiness and certain parameters related to vehicle as well as the driver [1] and[2]. Sleep onset detection can be used to prevent driver drowsiness that gives major implication in transportation system safety. EEG signal has been found to be the most predictive and reliable indicator of detecting the onset of sleep [1]. Therefore, it is important to understand the characteristics of EEG signal in order to determine when the drowsiness begins.

Fractal geometry is a new language used to describe, model, and analyze complex form or curves found in nature. FD can be considered a relative measure of the number of basic building blocks that form a pattern. This particular feature has been used, with great success in a variety of applications in biomedical science for transient detection, waveform com‐plexity estimation, pattern recognition, etc. Ones area in which FD analysis has been particularly useful is in the analysis of EEG to characterize neurophysiological states (Esteller et al., 1999).

FD is a measure of the signal complexity that can characterize different path physiological conditions. It provides an alternative technique for assessing signal complexity in the time domain, as opposed to the embedding method of assessing this complexity by reconstructing the attractor in the multidimensional phase space. This innovation permits a direct con‐nection between complexity variations and EEG changes over time, providing a fast computational tool to track nonstation‐arities in this signal. The FD also has the advantage of the data volume reduction. It is calculated over time in an overlapping sliding window, which greatly reduces the number of the data points stored. The exact amount of the data depends upon the sliding window size and the overlap used for the analysis (R. Esteller, 1999).

FRACTAL DIMENSION

FATIMAH ABDUL HAMID

Department of Marine Electric and Electronics Technology Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur

___________________________________________ Corresponding author: [email protected]

Received: 21st April 2011, Revised: 10th October 2011, Accepted: 10th October 2011


Volume 2 (2) 2011 14

A fractal curve in an n‐dimensional space has topological dimension n, and a non‐integer or fractional dimension called fractal dimension. It also possesses the characteristic that each portion of it can be considered a reduced‐scale im‐age of the whole for all time scales, then the curve is said to be self‐similar. Many algorithms developed to estimate the FD are based on the assumption of self‐similarity and independence of scaling (Esteller et al., 1999).

Fractal Dimension Algorithms


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The FD compares the actual number of units that compose a curve with the minimum number of units required to re‐produce a pattern of the same spatial extent. FDs computed in this fashion depend upon the measurement units used. If the units are different, then so are the FDs. Katz’s approach solves this problem by creating a general unit or yardstick: the average step or average distance between successive points, a. Normalizing distances in (3) by this average results in (5)

Implementation of Fractal Dimension Method

The electroencephalogram (EEG) signal is the extra‐cellular current created by cerebral electrical activity and has very weak amplitude in order of Volts. To obtain the EEG recordings, eighteen surface electrodes are placed at specific loca‐tions on the subject’s scalp using the international 10‐20 systems and connected by wires to an EEG machine. In practice, four bands of frequency for spontaneous activities can be distinguished, namely the delta rhythm with frequencies of less than 4 Hz, the theta rhythm in the range of 3.5 – 7.5 Hz, the alpha rhythm in the range of 8 – 13 Hz and the beta rhythm > 13 Hz.

In this work, the EEG data recorded from three normal and healthy male subjects (aged between 23 ‐31 years) were

analyzed. The recording was done at a sampling rate of 256 Hz. During recording, subjects were requested to perform brain‐related activities such as reading and performing simple tasks (such as mental calculation). Subjects were seated in a sound‐controlled room with dim lighting and air‐conditioner unit was switched on to provide extra comfort. They were also asked to abstain from taking excessive caffeine and naps on the day prior to testing. Additionally, the subjects were asked to reduce their sleep during the night prior to testing so that they shall be deprived from their sleep.

The properties of fractal dimension were studied using simulated sine wave signal. Several tests had been done to the

signal which is pure sinusoids without noise and sinusoids signal with noise had been added. The test also had been done to EEG signal.

Results

Based on the simulation analysis using the two methods, result shows that the FD values changes with respect to the change in frequency for pure sinusoidal signal as shown in Figure 1. However by adding the noise with standard deviation of two to the signal causes the FD to fluctuate as indicate in Figure 2.Repeating the same test with mixed signals confirms that noise causes the FD to fluctuate as shown in Figure 3 and Figure 4. Besides that, Higuchi’s method can be seen to pro‐duce higher FD values compares to Katz’s. Performing the same test on a real EEG signal gives the result as indicated in Figure 5. A 10 second time frame of an unknown state of EEG signal has been selected. Figure 5 show that the FD values varied with time which suggests the possibility that the selected EEG signal contained nose.

Expression (6) summarizes Katz’s approach to calculate the FD of a waveform.


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Figure 1: (a) Higuchi’s and (b) Katz’s fractal dimension plot for synthetic signal. The signal is a 8 Hz sine wave in beginning and end. In the middle is 12 Hz sine wave.


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Figure 2: (a) Higuchi’s and (b) Katz’s fractal dimension plot for synthetic signal. These are the examples of 10 s time series with 2 s with 8 Hz sine wave in the beginning and end. In the middle, 6 s 12 Hz sine wave, noise with standard

deviation of 2 was added to time series.


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Figure 3: (a) Higuchi’s and (b) Katz’s fractal dimension plot for synthetic signal. These are examples of 10 s time series with 1 Hz, 4 Hz, 8Hz and 13 Hz sine wave.


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Figure 4: (a) Higuchi’s and (b) Katz’s fractal dimension plot for synthetic signal. These are examples of 10 s time series with 1 Hz, 4 Hz, 8Hz and 13 Hz sine wave, noise with standard deviation of 2 was added to time series.


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Figure 5: (a) Higuchi’s and (b) Katz’s fractal dimension plot for 10 s EEG (PO7‐O1).


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Discussion and Conclusions The results obtained indicates that fractal dimension value increase with frequency. However, fractal dimension value varied when noise had been added. Further studied are needed to choose optimal filtering. Therefore, FD is able to clas‐sify EEG signal according to frequency band. References Ali Shoeb, John Guttag. (2003). ‘Patient‐Specific Seizure Onset Detection’. MIT Laboratory for Computer Science. Lal S.K.L. and Craig A. (2001). “A critical review of the psychophysiology of driver fatigue.”Biological Psychol‐ogy.55:173194. Robert D. Peters, Esther Kloeppel, Elizabeth Alicandri, Jean E. Fox, Maria L. Thomas, David R. Thome, Helen C. Sing, a Sharon M. Balwinski.”Effects of Partial and Total Sleep Deprivation On Driving Performance. “ (online) http://www.tfrc.gov/humanfac/sleep/sleepweb.htm (11 Nov. 2002) R. Esteller, G. Vachtsevanos, J. Echauz , T. Henry, P. Pennell C. Epstein, R. Bakay, C. Bowen, and B. Litt. (1999) ‘Fractal dimension characterizes seizure onset in epileptic patients’. Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’99), Phoenix, AZ. Vol. 4, No. 1851, pp. 2343‐2346. R. Esteller, G. Vachtsevanos, J. Echauz, and B. Litt. (2001). ’A comparison of waveform fractal dimension algorithms’. IEEE Transaction On Circuit and Systems‐I:Fundamental Theory and Applications, Vol. 48, No. 2. R. Esteller, G. Vachtsevanos, J. Echauz, and B. Litt. (1999). ’A comparison of fractal dimension algorithms using syn‐thetic and experimental data’. Proc. IEEE Conf. Circuit Systems, Orlando, FL.

http://www.tfrc.gov/humanfac/sleep/sleepweb.htm





Volume 2 (2) 2011 22

Abstract

The basic requirement for any ship is that it must have sufficient buoyancy to support the weight of the ship. However, as will be shown in the following sections, this may not be sufficient for a static equilibrium. Therefore, ships must satisfy not only the buoyancy condition but also a static equilibrium condition (Principles of Naval Architect, 1988). The requirements for adequate stability, directly affect the design of ship’s hull form and general arrangement. In this paper a barge of length 35 metres was selected as shown in Figure 1. The computation of the KG values was made using Maxsurf Suite of software. A table of KG values that complied with IMO Criterions was compiled. Keywords: IMO Criterion, Stability, Metacentric Height Introduction Measurement of Stability

The difference between the centre of gravity and the metacentre is defined as the metacentric height (GM) and this distance can be used for the initial stability of a ship at small angles of heel, from 00 to 50‐100. For small angles of heel the metacentric height (GM) is calculated by subtracting the height of the ship’s centre of gravity above the keel (KG) from the height of metacentre above the keel (KM), (Principles of Naval Architect, Intact Stability, 1988) i.e The height of metacentre above the keel is calculated by the summation of the height of centre of buoyancy above the keel (KB) and the metacentric radius (BMt) as follows where the metacentric radius is the distance between the centre of buoyancy and the metacentre. Therefore;

It is evident that GM is the key indicator of initial transverse stability as shown in Figure 2. Whilst it should obviously be positive, too high values should be avoided. GM is a measure of the ship’s stiffness in roll motion and largely governs the period of roll motion. Too high a value of GM leads to a very short roll period (Principles of Naval Architect, Section 3,

APPLICATIONS OF IMO STABILITY CRITERIONS TO DETERMINE THE OPERATIONAL LIMIT OF A BARGE

HAMDAN NURUDDIN

Department of Marine Design Technology Malaysian Institute of Marine Engineering Technology

Universiti Kuala Lumpur

Received: 10th October 2011, Revised: 25th November 2011, Accepted: 21st December 2011



Volume 2 (2) 2011 23

The actual value of GMt for a ship may be found by an inclining experiment. At the initial stages of design, to ensure that the ship has sufficient initial stability, the metacentric height can be calculated by using approximate formulae,

The results of the righting arm calculations for a ship are plotted as a set of cross curves known as cross curves of sta‐bility. These curves are used to determine the length of the righting arm at any angle of inclination for a given displace‐ment. A typical set of cross curves is shown in Figure 3. The range of displacements over which cross curves have been determined is from the light ship displacement at the lower end to a displacement usually well above the load displace‐ment, so that stability can be assessed at deep draughts associated with potential flooding situations (Principles of Naval Architect, Section 3, Intact Stability 1988).

Figure 1: The 35 m barge that was used in the calculation procedures


Volume 2 (2) 2011 24

Since the centre of gravity is a function of loading condition the basis of the cross curves is taken as a fixed point, such as the keel (K). Then the righting arm is

Figure 2: Transverse Section of an Inclined Vessel

Figure 3: Typical cross curves of stability


Volume 2 (2) 2011 25

Statical Stability Curve Cross curves of stability are a convenient form in which to store the information necessary to determine the large angle stability characteristics of a ship at any displacment, but at a single assumed position of the centre of gravity. For the ship operator as well as for the naval architect during the design process, what is needed is a determination of the righting arms or moments of a ship heeled to any angle while in a given loading condition at one displacement and with its centre of gravity at a position different from the one that was assumed in preparing the cross curves. The statical stability curve in which righting arms are plotted against angle of heel is the appropriate format. The statical stability curve is determined by picking values of the righting arms from the cross curves at the appropri‐ate displacement and correcting the values thus obtained to reflect the actual position of the centre of gravity. The conventional plotting of a statical stability curve is shown in Figure 4. Since the centre of gravity is at centreline, the direction of assumed heel (starboard or port) is immaterial, because the centreline symmetry of the hull would cause the centre of buoyancy to assume symmetrically corresponding to the positions on either side at any given angle of heel. Although the curve can be plotted for all angles of heel for which cross curves have been determined, it is typically termi‐nated where the GZs become negative, that is, where righting arms change to capsizing arms (Principles of Naval Archi‐tect, Section 3, Intact Stability 1988).

Intact Stability Criteria Stability is one of the most important safety features of ships, and in particular of small ships which tend to suffer from insufficient stability which could lead to capsizing the vessel and loss of the crew. It is, therefore, essential to design a ship with adequate stability and to maintain it in all conditions of loading during its operation (Principles of Naval Archi‐tect, Section 3, Intact Stability 1988).

The types of stability criteria can be divided into the following groups;

1. GM or initial stability 2. Wind heel 3. GZ or quasi dynamic stability 4. Energy balance 5. Wave adjusted stability 6. Dynamic motion stability

Figure 4: Typical statical stability curve


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Based on recommendations from the 1960 International Conference on the Safety of Life at Sea (SOLAS 60), the IMCO sub‐committee on Subdivision and Stability was formed in 1962. The first international stability criterion, Resolution A.167, largely based on Rahola’s GZ criteria, was adopted by the IMO in 1968 for ships under 100 m. The IMO assembly adopted Resolution A.562 in 1985. This resolution is an energy balance criterion, but also includes a wind heel recommendation, and is to be used as a supplement to A.167. Criteria based on GM or Initial Stability

GM is the most basic stability criterion and one of the earliest methods used to quantify a ship’s stability. Specifica‐tion of a minimum value of initial GM and freeboard sufficed as the sole numerical stability criterion in use until 1940s. Many national and international regulations have a minimum GM as one component of their requirements since a value of GM is easy to calculate, its meaning is relatively simple to understand, and the effect of its magnitude on the heel re‐sponse is readily predictable. However, since the position of the metacentre varies as the ship heels, GM is only a valid measure within small angles of the initial unheeled position. In most cases, GM tells little about the character of the vessel other than very small angles of heel (Principles of Naval Architect, Section 3, Intact Stability 1988).

The use of GM based criterion on two different types of ships, shown in Figure 5, serves well to illustrate the problem in choosing criteria to represent a type rather than the form of the vessel. The much greater initial GM of the tug is mis‐leading. The high value of initial GM does not reflect the tug’s greatly shortened range of positive stability compared with a conventional cargo vessel, or its low value of maximum righting arm and low value of the angle at which that maximum occurs.

The principal strength of GM based criteria lies in their simplicity and their accuracy in predicting equilibrium heel angles when very specific heeling moment descriptions can be provided. For this reason, GM has been widely used in the past in criteria that establish a maximum heel angle under the influence of such forces as those due to lateral wind load‐ing, towline pull, lifting heavy weights over the side, passenger group movements, steady high‐speed turning, and others (Principles of Naval Architect, 1988).

Figure 5: Comparison between stability curve of a tug and cargo vessel


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Despite these shortcomings, GM is still used as useful stability criteria for special cases. Typical examples of specific GM based stability criteria are given below. All Ships: IMO A749 require that for all ships greater than 24 m in length the initial metacentric height GM0 should not be less than 0.15 m. Passenger vessels: For passenger vessels, IMO A749 requires that the heel angle on account of passengers to one side should not exceed 10 degrees. A standard weight of 75 kg per passenger and four persons per m2 are assumed. Criteria based on Wind Heel and Rolling (Weather Criterion) [International Maritime Organisation A749] Wind heel criteria are based on the principle of a heeling moment created by a pressure on the lateral profile of a ship coupled with a drag force on the underwater hull. This heeling moment is evaluated against the righting moment (either based on GM or the righting lever) to limit heel to a specified angle. IMO A749 requires that the ability of a ship to withstand the combined effects of beam wind and rolling should be demon‐strated for each standard condition of loading as follows:

i. The ship is subjected to a steady wind pressure acting perpendicular to the ship’s cen treline which results in a steady wind heeling lever (LW1)

ii. From the resultant angle of equilibrium ( o), the ship is assumed to roll owing to wave action to an angle of

roll ( 1) to windward. Attention should be paid to the effect of steady wind so that excessive resultant an‐gles of heel are avoided. The angle of heel under action of steady wind should be limited to a certain angle (16 deg. or 80% of the angle of deck edge immersion, whichever is less).

iii. The ship is then subjected to a gust wind pressure which results in a gust wind heeling lever (LW2)

iv. Under these circumstances, area b representing the righting energy should be equal to or greater than area a

representing the capsizing energy a as shown in Figure 6.

Figure 6: IMO Criterions based on the areas of the GZ Curve


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IMO criterion for Barges For all barges the following are the criterion which must be met.

i. The area under the righting lever curve up to the angle of maximum righting lever should not be less than 0.08 m radian [IMO criterion # 1].

ii. The static angle of heel due to a uniformly distributed wind load of 0.54 kPA (wind speed 30 m/s) shall not

exceed an angle corresponding to half the freeboard for the relevant loading condition, where the lever of wind heeling moment is measured from the centroid of windage are to half the draft [IMO criterion # 2].

iii. The minimum range of stability should be;

For L <= 100 m ‐ 20 degrees For L >= 150 m ‐ 15 degrees For intermediate lengths the range is found by interpolations [IMO criterion # 3]. Classifications societies required that the designers submit the stability booklets with the graphs of all three criterions (Bureau Veritas Rules for Barges, 2001 Methodology

A barge of length 35 metres in length was modelled in Maxsurf Pro Version 16 (2011). Then the file was opened in Hydromax Pro Version 16 (2011). A range of loads with the KG values were inputted in the loadcase table. For the IMO#1 Criterion, a Limiting KG Analysis was used to calculate the acceptable KG Range for various displace‐ments. A Graph of KG against Displacement was plotted in Figure 7. The data is tabulated in Table 1

Figure 7: Plotted of all three IMO Criterion and the VCGs of the Barge


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For IMO#2 Criterion, a Large Angle Analysis was used. The values for projected wind areas and the centre of wind heeling moment were calculated and inputted in the Criteria Dialogue Box. An iterative process was used till the KG and heel angles met the IMO criteria.

For IMO#3 Criterion, a Large Angle Analysis was used and the IMO criteria in the Criteria Dialogue Box were selected. A heel angle of 20 degrees was used in the Criteria Dialogue Box. An iterative procedure was performed to determine the acceptable KG values for various displacements. A Graph of KG against Displacement was plotted. Figure 8 through Figure 10 shows the flow chart for all the three criterions.

Figure 8: Flow Chart to Calculate the IMO 1st Criterion in Maxsurf Suite

Figure 9: Figure 6: Flow Chart to Calculate the IMO 2nd Criterion in Maxsurf Suite


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Figure 10: Figure 6: Flow Chart to Calculate the IMO 3rd Criterion in Maxsurf Suite

Table 1: Results for Criterion 1, 2 and 3


Volume 2 (2) 2011 31

Conclusion The calculating procedures used were quite tedious. A thorough understanding of the principles of the IMO Criteria was essential in order to perform the above procedures. Besides that, the user must be well verse with using the Maxsurf Suite of Software. From the study, the allowable KGs which the barge is allowed to operate are below the blue line. Any value above the blue line is regarded as not in compliance with IMO requirements for safe operation of the vessel. Under the normal rules of the maritime industry, the barge is liable for severe penalty by the Flag State should it operate above the stipulated line. References Principle of Naval Architecture (1988). Society of Naval architecture and Marine Engineers, Volume 1, New Jersey, New York. (www.sname.org) Maxsurf Manual (2011). Formation Design System, Version 16. (www.formsys.com) Hydromax Manual (2011). Formation Design System, Version 16. (www.formsys.com) Bureau Veritas Rules for Barges (2001). Bureau Veritas.


Volume 2 (2) 2011 32

Abstract

Underwater images viewing are very important tools for the purpose of scientific research and technology such as archae‐ology investigation, undersea lives identification, sea floor explorations and others undersea activities. An advance under‐water image viewing with no limitation of all aspect or parameters of viewing should be useful for military actions. A lot of causes have been identified to improve the quality of underwater images which suffers from limited range of visibility, non uniform lighting, low contrast, colour diminished, important blur and etc. The problems of underwater images are also come from light absorption and scattering which spread in the water, water or sea surfaces formations either concave or convex regions, the quality of water, the environment and the degradation effects. All the causes will affect the quality of underwater still images and video such as the domination of one colour on the images, the creation of temporal illumi‐nation patterns, specification of transmission properties of light in the water, degradation and so on. Current research present a lot of algorithm based on the above problems. Several techniques have been tested and a lot of filters have been used in order to produce a clear underwater image. A good combination of technique and filters need to be consid‐ering for this purpose.

Keywords: underwater image, pre‐processing, underwater vision, filter

Introduction

Nowadays, the underwater imaging is widely used in scientific research and technology. The Unmanned Underwater Vehicle (UUV), Autonomous Underwater Vehicles (AUV) or submarines are equipped with vision system to explore and survey the ocean floor. Image processing is the core subject work with the computer vision methods to improve the clarity of underwater and used for various applications such as mine detection inspection of underwater power and telecommu‐nications cables, pipelines, nuclear reactor and columns of offshore platforms. A large number of works have been pub‐lished in the last decade on this subject. The improvement of underwater image processing techniques and methods has triggered a lot of underwater research activities and technology, such as for marine biologist, archaeologist and mapping. Moreover, underwater photography is becoming more accessible to the public. Figure below shows the autonomous un‐derwater vehicle and unmanned underwater vehicle.

ENHANCEMENT OF UNDERWATER IMAGES

AHMAD ZAWAWI BIN JAMALUDDIN

Department of Marine Electrical and Electronics Technology

Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur.

Received: 4th October 2011, Revised: 2nd December 2011, Accepted: 23rd December 2011



Volume 2 (2) 2011 33

The underwater image problem has been faced up with different approach: neural network, principal components, independent components and etc.

Most computer vision methods cannot be employed directly underwater. This is due to the particularly challenging environmental conditions, which complicate image matching .The limitation of visibility, transformation of colour, absorp‐tion of illumination, the effect of small particles such as plankton and the characteristic of water are the main problem when talk about underwater vision. Figure 2 shows an archaeological site around 2.5 meters under the sea surface.

It is easy to see that the visibility degradation effects vary as distance to the object increase. It can be see that the front object is clearer than the rear object.

Figure 1: The Autonomous Underwater Vehicle or Unmanned Underwater Vehicle.

Figure 2: The underwater Mediterranean archaeological site. The visibility and colour quickly degrade as a function of distance.


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A major difficulty to process underwater images comes from light attenuation (Figure 3). It limits the visibility dis‐tance. The light attenuation process is caused by the absorption which is remove light energy and scattering which is changes the direction of the light path. Water tends to absorb light with longer wavelengths (yellow and red), while scat‐tering light with short wavelengths (blue and green). This is why sea water appears blue or green. The amount of absorp‐tion depends greatly on the purity of water, but it is also dependent on the depth of water. Figure 4 shows that as the depth of water increases, the bandwidth of light that passes through the water increase. This cause a problem for under‐water vision as the absorption of light makes it get dark very quickly as the depth increase. Since different frequencies are absorbed at different rates, image tends to lose all colour information. Figures 3 and 4 below show the effect of sea sur‐face and depth to the underwater illumination and colour appearance.

Figure 3: The effect of sea surface to the underwater illumination.

Figures 4: The colour appearance in underwater depend to the depth from the sea surface.


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Another well known problem concerning the underwater images is related to the density of sea water, which is considered 800 times denser than air. This mean that, salt’s molecule will reduce the underwater illumination. The physic theories of light proved that the reflected amount of light is partly polarised horizontally and partly enter the water verti‐cally. An important characteristic of the vertical polarisation is that it makes the object less shining. The illuminations of underwater also depend to the sea surface. The illumination under the wavy surface is different compare to the flat sur‐face. The structure of sea surface will affect the reflection of ray light in the water. These spatiotemporal patterns modu‐late the reflectance and texture of the bottom of the sea. The light refraction effect shows in figure below.

Light is the

most important elements to view a clear underwater image. The natural light from the sun is a common light source but it is only available for certain depth from the water surface. The view on the sea floor is darker than the sea surface. Artifi‐cial light solves the problem of underwater illumination. In some cases, but its failed to illuminate underwater image for certain application. This is due to the characteristic of artificial light which is otherwise different comparing to the natural light. Artificial light will spot only on the object but the natural light illuminate the object and the environment surround the object. Low illumination will affect the clarity and the precision of image. Figures 6 and 7 below show the different between the artificial light and sunlight.

Figure 5: The light refraction effects caused by waves on the water surface.

Figure 6: Photo shows that the artificial light is only spot to the front object.


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The distance between the object and camera will increase the prominent blue colour on the image. If the camera is too far from the object, much blue colour will affect the image and other colour will disappear in relation to the deep from the sea surface. The distance between the camera and the object must be closer possible to avoid the blue and green col‐our effect. On the other side, the floating particles are also affecting the quality of the image by increasing the effect blur‐ring.

The floating particles modify the colour and produce a bright artifact known as marine snow. Large particles such as silt caused light to be scattered in all direction which causes the contras in an image decrease rapidly as depth increases and it is also cause blurring in images making it hard to distinguish an objects from background. Figure 8 show the effect of marine snow to the underwater image.

Methods of underwater image enhancement.

1. Underwater Image Pre‐Processing The underwater still or video image suffer from limited range, non uniform lighting, low contrast, diminished colour, important blur and so on. Besides that, many parameters can modify the optical properties of the water and underwater image show large temporal and spatial variations. Pre‐processing methods typically only concentrate on non uniform lighting o colour collection and often require additional knowledge of the environment such as depth, distance object to camera or water quality. Figure 9 shows the algorithm of the method. Pre processing reduces underwater perturbations and improves image quality. The algorithm composed several suc‐cessive independent processing steps which respectively correct non uniform illumination, suppress noise, enhance con‐trast and adjust colour.

Figure 7: Photo shows the effect of sunlight to the underwater images.

Figure 8: The example of marine snow appeared in underwater.


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Raw images An image Figure 10 consist a lot of perturbation and noise.

Pre processing filter

a. Removing potential moiré effect. Moiré effect is the appearance of wavy repetitive pattern on image. It is not an underwater perturbation and it is often considered as aliasing phenomena.

Removing the moiré effect is important because the following processes enhance contrast, so enhance the moiré effect and consequently highly degrade effect result.

Since the Moire effect on the image above is in diagonal from left to right direction and it can be removed via spectral analysis by deleting peaks 1 and 2 in Fourier transform.

Figure 9: Algorithm Pre Processing of Underwater image.

Figure 10: Raw image.


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The result of this process showed in Figure 12.

b. Resizing and extending symmetrically the image to get a squared image whose size is a power of two. Symmetri‐

cal extension to prevent from potential border effect and resizing squared image can speed up the following proc‐ess by enabling to use fast Fourier Transform and Fast Wavelet Transform algorithms.

Figure 11: Spectral analysis.

Figure 12: Result after remove moiré effect.

Figure 13: Resizing previous image.


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c. Converting colour space from RGB to YCbCr (Luminance Chrominance) The colour space conversion allows working only in one channel instead of work repetitively on Red, Green and Blue channels. In YCbCr, the luminance channel (Y) is corresponding to intensity component (gray scale image) and it is the only component processed in this step. This will speed up the process compare to the RGB channel.

d. Homomorphic filtering. This filter is used to correct non uniform illumination and to enhance contrast on the image. Figure 15; shows the result after using homomorphic filter. Frequency filter has been selected for this purpose because it’s correct non uniform lighting and sharpens the edges at the same time.

e. Anisotrophic filter

Anisotrophic filter used to simplify image features to improve image segmentation. This filter smoothes the image in homogeneous area but preserves edges and enhances them. It is used to smooth textures and re‐duce artifacts by deleting small edges amplified by homomorphic filtering. Figures 16; show the result. Image (before): A lot of texture appeared on the image caused by homorphic filter. Image (after): After using anisotro‐phic filter, all the textures and artifacts have been suppressed.

Figure 14: Converting colour space from RGB to YCbCr

Figure 15: Result after using homomophic filter.


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This filter used to suppress noise which was amplified by homomorphic filter. Figure 17; show the image after wavelet de‐noising. This method was preferred because of it performance speed in comparison of its de‐noising quality.

f. Adjusting image intensity

This filter is used to increases image’s contrast by adjusting image intensity values. Equation 1, show the mathe‐matics explanation on image intensity. It will suppress eventually outliers’ pixels to improve contrast stretching. It

then stretches contrast to use the whole range of intensity channel.

Figure 16: Image using anisotrophic filter

Figure 17: Adjusting image intensity


Volume 2 (2) 2011 41

g. Converting Back YCbCr to RGB and Reverse Symmetric extension. After adjusting image intensity, to regain colour, the image need to convert to RGB space. Then, the symmetrical extension need to be cut to regain the original size. Figure 18; show the result.

h. Equalizing colour mean. In underwater imaging color channels are rarely balanced correctly. One of the problems of underwater image viewing is the predominant of blue and green colour. This final step will suppress predominant colour by equaliz‐ing RGB channel means. The final result shows in Figure 19. It can conclude that the predominant blue and green colour and also noise on the image have been removed. The result shows a good balance of colour in RGB space.

2. Integrated Colour Model Others method to enhance underwater image is by using integrated colour model. This method gives the solution to solve the problem of light absorption, the scattering effect and inherence structural en‐vironments. An approach base on slide stretching has been proposed to solve the problem. The algorithm of this method is shown in Figure 20.

Figure 18: Convert colour space from YCbCr to RGB

Figure 19: Final result.


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First, the contrast stretching applied on the raw image in the RGB space. The purpose of this step is to equalize the colour contrast. Then, the image will be transform to HSI (Hue Saturation Intensity) space. The second contrast stretching will be applied on the HIS image to increase the true colour and solve the problem of lighting. Figure 21; show the block diagram of the process.

Figure 20: Algorithm of the process.

Figure 21: Block diagram of the process.


Volume 2 (2) 2011 43

The HSI (Hue Saturation Intensity) model provides a wider range of by controlling the colour elements of the images. The colour elements are S (Saturation) and I (Intensity). For example, if images dominate by blue colour, S and I can be controlled to get a range of light blue and dark blue. By this technique, contrast ration also can be controlled the underwa‐ter images. For the grey level pixel, by employing the histogram, contrast stretching will used to enhance the contrast of the image by stretching the range of the colour value to make use of all the possible value. The normalization pixels can be calculated by using function in equation (2). Where

PO = the normalized pixel value. Pi = the considered pixel value. a = the minimum value of the desired range. b = the maximum value of the desired range. c = the lowest pixel value currently present in the image. d = the highest pixel value currently present in the image.

The contrast stretching method is very practical for grey level images. When the same contrast stretching algo‐

rithm is applied to colour image, each channel (Red, Green and Blue) is stretched using the same scaling to maintain the correct colour ratio.The first step of this algorithm is to balance the red and green channel to be slightly the same to the blue channel. This is done by stretching the histogram into both sides to get well spreads histogram. In the second step, the RGB image will transform to HSI image using the saturation and intensity transfer function. The purpose is to increase the true colour and the brightness of underwater images. The function will stretch the saturation and intensity values of HSI colour model. The true colour of underwater images will be generating from the saturation parameter. The HSI space also helps to solve the lighting problem by using the intensity parameters. Figure below show the final result using inte‐grated colour model.

It can be conclude that the image after enhancement is clearer than the image before enhancement. The quality of images is statically illustrated through the histograms by using the slide stretching algorithm for both on RGB and HSI col‐our model

Figure 22: Final result using integrated colour model.


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Conclusion Underwater imagery is recognized as a useful tool for objects detection, objects recognition or for studies of sea life‐form populations and oceanic resources. However, underwater scenes are usually veiled by the light interaction with the medium: images present low contrast and luminosity, and visibility is reduced. Moreover the colour perception is affected and the turbidity due to suspended matter causes scattered illumination, termed in‐scattering. The different method and algorithm such as a pack of filter for pre‐processing to reduce noise and interference on the images, slides or contrast stretching for both RGB and HSI colour model, removing attenuating natural flicker patterns, eliminate of degradation effect by using polarizer, removing the illumination consistencies under strong refracted sunlight and etc have been purposed for the same objective which is to improve underwater image quality. Both algorithms were successfully proving their result either theoretically nor experimentally. The different among them is in the area of application. For example, a video image will try reducing processing time to avoid delay. Methods which have a lot of process such as Automatic Underwater Image Pre‐Processing is not suitable for certain application because of the processing time. However, methods of underwater image enhancement have increased the underwater activities, from underwater archaeological and seabed exploration until underwater recreation, researchers, scientist and individual gain a lot of benefits. Finally, a lot of works will need to do from time to time to improve the underwater image enhancement tools. References Yaov Y. Schechner and Nir Karpel, “Attenuating Natural Flicker Patterns”, Proc. MTS/IEEE Oceans’04, Vol 3, pp.1261‐1268 (2004).

Yaov Y. Schechner and Nir Karpel, “Clear Underwater Vision”, Proc. Computer Vision & Pattern Recognition, Vol. 1, pp. 536‐543 (2004).

Nuno Gracias, Shahriar Negahdaripour†, Laszlo Neumann, Ricard Prados, Rafael Garcia, “A motion compensated fil‐tering approach to remove sunlight flicker in shallow water images”, Ocean 2008, pp.1‐7, (2008).

[Julia Åhlén, “Colour correction of underwater images using spectral data”, Digital comprehensive summaries of Upp‐sala Desertations from the Faculty of Science and Technology, University of Uppsala., 2005.

Atsushi Yamashita, Megumi Fujii and Toru Kaneko, “Color Registration of Underwater Images for Underwater Sensing with Consideration of Light Attenuation”, Department of Mechanical Engineering, Shizuoka University, Japan., ICRA, pp. 6, 2007.


Volume 2 (2) 2011 45

Abstract

Depending of the industries and the type of products or services, costs of quality (costs associated to poor quality) are typically 3 to 6 times as large as profits. It has been the practices of the world leading companies to measure the cost of quality towards cost reduction, greater profits, competitiveness and total customer satisfaction. It is still quite unknown whether costs of quality are being measured, analysed and efforts being made to reduce them in Malaysian Shipbuilding, Ship Repairing and Offshore structure construction industries. The objective of this paper is to provide a proposal as well some guidelines for students’ Final Year Project (FYP) to conduct a study on the topic similar to this paper’s title. The ob‐jectives, the expected outcomes and the basic methodology of the proposed research are mentioned below. As a general guidelines some literature review on quality, some industrial experiences from quality perspective and an overview of the industries under study are also outlined in this paper.

Keywords: Quality, Shipbuilding, cost of quality, optimization. Introduction

The research are aimed to assess the size of the quality problems (if possible in terms of Costs of Quality) faced by the industries, to identify and document the quality practices of the companies of the mentioned industries, to determine the relationship of the quality problems and the quality practices and to determine the best practices of the world‐class com‐panies of the relevant industries. It is expected that data on the nature and size of quality problems (if possible quality costs) faced by the Malaysian related industries, the quality practices of the Malaysian companies/industries, the correlation of quality problems to the quality practices and the data on the current best practises of the local and international companies as a benchmarking will be obtained from the research. From the results obtained, recommendation of the best quality practices for the Ma‐laysian Shipbuilding, Ship Repairing and Offshore Structure Construction will be discussed to optimize the quality imple‐mentation towards greater competitiveness.

OPTIMIZATION OF QUALITY IMPLEMENTATION IN SHIPBUILDING, SHIP REPAIRING AND OFFSHORE CONSTRUCTION IN MALAYSIA TOWARDS

FAUZUDDIN BIN AYOB

Department of Marine Design Technology Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur


Received: 15th November 2011, Revised: 25th November 2011, Accepted: 25th November 2011


Volume 2 (2) 2011 46

Methodology

A detail theoretical study and research review will be conducted to understand the concepts of quality, cost of quality and the various quality initiatives such as Quality Planning, Quality Control and Quality Improvement, ISO 9000, TQM, Six‐Sigma, SPC, Benchmarking, Lean Production, etc. The basic operations and process flow of the industries will also be iden‐tified. The objectives and the expected outcomes of the research will be grasped to produce planning and programs for the project implementation.

A survey on the mentioned industries will be conducted to collect data, measure and analyse the nature and size of quality problems (if possible costs of quality) faced by the companies as well to document the quality practices that are currently adopted by the companies. Appropriate approaches and methods of data collection are to be established.

A correlation between the quality performance and quality problems against the quality practices will be constructed and determined. Problem solving methodology and statistical tools and techniques will be employed in these processes. A research review will also be conducted to determine the best practices of the world leading companies of similar and other industries including manufacturing as a benchmark for the industries under studied.

Discussion, suggestion and recommendations will be documented and presented as a report for the local industries benchmarking towards improvement of quality implementation and ultimately for greater competitiveness.

Literature Review

1. Cost of Quality

The cost of poor quality (COPQ = PONC):

“COPQ is the sum of all costs that would disappear if there were no quality problems.”‐ Juran

“You can easily spend 15 ‐ 30% of your sales dollars on PONC.” – Crosby

“In most companies the costs of poor quality runs at 20 ‐ 30% of sales.” – Juran

Something to think about ……….

Net profits for many companies is less than 5% of sales

COPQ on the average is 17% of sales

Total COQ on the average is 25% of sales

COPQ is some companies is as high as 40% of sales

COPQ is typically 3 to 6 TIMES as large as profits


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2. Categories of Quality Costs

Many companies summarize these costs into four categories. Some practitioners also call these categories the “cost of quality.” These categories and examples of typical subcategories are discussed below.

Internal Failure Costs.

These are costs of deficiencies discovered before delivery which are associated with the failure (nonconformities) to meet explicit requirements or implicit needs of external or internal customers. Also included are avoidable process losses and inefficiencies that occur even when requirements and needs are met. These are costs that would disappear if no deficiencies existed.

a) Failure to Meet Customer Requirements and Needs.

Examples of subcategories are costs associated with: Scrap: The labor, material, and (usually) overhead on defective product that cannot economically be repaired. The titles are numerous—scraps, spoilage, defectives, etc. Rework: Correcting defectives in physical products or errors in service products. Failure analysis: Analyzing nonconforming goods or services to determine causes. Scrap and rework—supplier: Scrap and rework due to nonconforming product received from suppliers. This also includes the costs to the buyer of resolving supplier quality problems.

b) Cost of Inefficient Processes.

Variability of product characteristics: Losses that occur even with conforming product (e.g., overfill of packages due to variability of filling and measuring equipment). Unplanned downtime of equipment: Loss of capacity of equipment due to failures.

External Failure Costs.

These are costs associated with deficiencies that are found after product is received by the customer. Also included are lost opportunities for sales revenue. These costs also would disappear if there were no deficien‐cies.

a) Failure to Meet Customer Requirements and Needs.

Examples of subcategories are Warranty charges: The costs involved in replacing or making repairs to products that are still within the warranty period. Complaint adjustment: The costs of investigation and adjustment of justified complaints attributable to defective product or installation. Returned material: The costs associated with receipt and replacement of defective product received from the field.

b) Lost Opportunities for Sales Revenue.

Examples are Customer defections: Profit margin on current revenue lost due to customers who switch for reasons of quality. An important example of this category is current contracts that are canceled due to quality. New customers lost because of quality: Profit on potential customers lost because of poor quality.


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Appraisal Costs (costs incurred to determine the degree of conformance to quality)

Examples are Incoming inspection and test: Determining the quality of purchased product, whether by inspection on re‐ceipt, by inspection at the source, or by surveillance. In‐process inspection and test: In‐process evaluation of conformance to requirements. Final inspection and test: Evaluation of conformance to requirements for product acceptance.

Prevention Costs (costs incurred to keep failure and appraisal costs to a minimum)

Examples are Quality planning: This includes the broad array of activities which collectively create the overall quality plan and the numerous specialized plans. It includes also the preparation of procedures needed to communicate these plans to all concerned. New‐products review: Reliability engineering and other quality‐related activities associated with the launch‐ing of new design. Process planning: Process capability studies, inspection planning, and other activities associated with the manufacturing and service processes.

3. Quality Management Practices: A Brief Overview

Table 1 depicts the Quality principles that have evolve over time

Table 1: Quality principles evolvement over time


Volume 2 (2) 2011 49

Artisan

Up until the advent of mass production, artisans completed individual products and inspected the quality of their own work or that of an apprentice before providing the product to the customer. If the customer experienced any dissatisfaction with the product , he or she dealt directly with the artisan

Inspection

Inspection refers to those activities designed to detect or find nonconformance existing in already completed products and services. Inspection, the detection of defects, is requlatory process.Inspection occuring only after the part or assembly has been completed can be costly. If a large number of defective product has been produced and the problem has gone unnoticed, then scrap or rework costs will be high.

Quality Control

Qualtiy control goes beyond inspection by

a) Establishing standards for the product or service, based on the customer needs, requirement, and expectations. b) Ensuring conformance to these standards. Poor quality is evaluated to determine the reasons why the parts or service provided are incorrect. c) Taking action if there is a lack of conformance to the standards. Implementing plans to prevent future nonconformance.

Statistical Quality Control (SQC)

Building on the four tenets of quality control , statistics were added to map the results of parts inspection . The use of statistical methods for production monitoring and parts inspection became known as statistical quality control (SQC) , wherein statistical data are collected, analyzed, and interpreted to sove problems.

Statistical Process Control (SPC)

Over time, companies came to realize that there was a need to be proactive when dealing with problems. Thus the emphasis shifted from utilizing statistical quality control methods for the inspection or detection of poor quality to their use in the prevention of poor quality. Prevention of defects by applying statistical methods to control the process is known as statistical process control (SPC). Statistical process control emphasizes the prevention of defects. Prevention refers to those activities designed to prevent defects, defectives, and nonconfromance in products and services.

Total Quality Management

As the use of statistical process control grew in the 1980s, industry saw the need to monitor and improve the entire system of providing a quality product or service. Sensing that meeting customer needs, requirements, and expectations involved more than providing a product or service, industry begin to integrate quality into all areas of operations, from the receptionist to the sales and billing departments to the manufacturing, shipping, and service departments. This integrated process improvement approach, involving all departments in a company in providing a quality product or service, known as Total Quality Management.


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Continuous Improvement

The Continuous Improvement (CI) philosphy focuses on improving processes to enable companies to give customers what they want the first time, every time. This customer‐focused, process‐improvement oriented approach to doing bussiness results in increased satisfication and delight for both customer and employess. Continuous improvement efforts are characterized by their emphasis on determining the best method of operation for a process or system. The key words to note are continuous and process.

Quality Standards

The most widely known of the quality standards are ISO 9000 and QS 9000. ISO 9000 was created to deal with the growing trend toward economic globalization. In order to facilitate doing business in a variety of countries, a series of quality standards was developed by the International Organization for Standardization. Applicable to nearly all organizations, the standards provide a baseline against which an organization’s quality system can be jugde. Eight key principles are integrated into the ISO 9000 standards : customer‐focused organization, leadership, involvement of people, process approach, system approach to management, continuous improvement, factual approach to decision‐making, and mutually beneficial supplier relationships.

Six Sigma Methodology

The six sigma concept was developed at Motorola Corporations as a strategy to deal with product and system failures. The increasing complexity of system and products used by consumers created higher than desired system failures rates. To increase system reliability and reduce failure rates, organizations follows the Six Sigma methodology which utilize a rigorous process‐improvement methodology‐‐‐define‐‐measure‐‐analyze‐‐improve‐‐control (DMAIC). This procedure encourages managing by fact with data and measurement tools, techniques, and systems.

Quality Evolution in Japan The quality evolution in Japan is depicted in Figure 1.

Figure 1: Quality Evolution in Japan


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Juran’s Quality Managerial Processes

Managing for quality makes extensive use of three such managerial processes such as Quality planning, Quality control and Quality improvement. These processes are now known as the Juran’s trilogy. The three proc‐esses of the Juran’s trilogy are interrelated as shown in Figure 2.

The Juran’s trilogy diagram is a graph with time on the horizontal axis and cost of poor quality on the vertical axis. The initial activity is quality planning. The planners determine who the customers are and what their needs are. The planners then develop product and process designs to respond to those needs. Finally, the planners turn the plans over to the operating forces: “You run the process, produce the product features, and meet the cus‐tomers’ needs.”

Chronic and Sporadic

As operations proceed, it soon emerges that the process is unable to produce 100 percent good work. Figure 2 shows that over 20 percent of the work must be redone due to quality deficiencies. This waste is chronic—it goes on and on. Why do we have this chronic waste? This is due to the operating process was planned that way. Under conventional responsibility patterns, the operating forces are unable to get rid of this planned chronic waste. What they can do is to carry out quality control to prevent things from getting worse. Figure 4.2 also shows a sudden sporadic spike that has raised the defect level to over 40 percent. This spike re‐sulted from some unplanned event such as a power failure, process breakdown, or human error. As a part of their job of quality control, the operating forces converge on the scene and take action to restore the status quo. This is often called “corrective action,” “troubleshooting,” “putting out the fire,” and so on. The end result is to restore the error level back to the planned chronic level of about 20 percent. The chart also shows that in due course the chronic waste was driven down to a level far below the original level. This gain came from the third process in the trilogy—quality improvement. In effect, it was seen that the chronic waste was an opportunity for improvement, and steps were taken to make that improvement.

Figure 2: Juran’s Trilogy Diagram


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Sharing of Industrial Experience: Quality Perspective

In the early of 1980’s, Quality was not much stressed in Malaysia’s organizations except in multinational manufactur‐ing/services company or company that affiliated with the foreign technology or management. Most of the time for local organizations, completing one’s job was the target of the day without much concerned on the quality of the output as well as productivity. There was almost no specific unit or group known as an inspection group, what more quality control/ quality assurance or other structured ways dealing with quality as established in multinational organizations. In the early of 1980’s, Quality Control Circle (QCC), small group/team formed of workers from the same work area that focussed on work/ process/ product/ quality improvement was introduced to Malaysia government offices and the statutory bodies including government link companies through the adoption of government’s concepts of ‘Look East Pol‐icy’. QCC was of Japanese origin started in 1960s and as in 1980 there were over 100,000 QCCs in operation in Japanese organization of all types. About the same time the United States visited their Japanese counterparts to learn (benchmarking) why Japanese quality was superior to theirs in many product lines. Many American companies in the US and their subsidiaries in Malaysia as well as the other European companies had adopted the QCC and other Japanese best practices. As from here on towards 1990’s QCC had grown in numbers like mushroom both in Malaysia’s government of‐fices and private companies including locals and foreign. Through this effort and other initiatives, more or less it had revo‐lutionised the perception of Malaysian workers towards quality. Inspection/Quality Control or Quality Assurance team/ unit or groups were later formed in many organizations in Ma‐laysia copying what being practiced by the foreign companies and later on widely implemented especially with the arrival of ISO 9000 in Malaysia in the early 1990. ISO 9000 has become the symbol of quality implementation and quality superi‐ority in many organizations in Malaysia as from mid of 1990s to 2000s more and more organizations of all types being cer‐tified with ISO 9000. At the same time QCC seemed to be faded out from many organizations in Malaysia for whatever reasons. Quality concepts of Quality Control, Statistical Quality Control, Statistical Process Control QCC and TQM as briefly de‐scribed above had long being adopted by many multinational companies especially the manufacturing sectors prior to the introduction of ISO 9000. Through the implementation of these concepts and other best practices that enabled the Japa‐nese products to concur the world markets started with the shipbuilding in the 1960s; automobiles, electrical and elec‐tronics, consumer products and other product lines in the 1970s, 1980s till 1990s when American started getting back their momentum. Besides benchmarking the Japanese on their quality concepts and other best practices, the American also invented the Six‐Sigma that managed to turn around their companies and competing again alongside with the Japa‐nese to be the world market leaders. ISO 9000 was merely adopted in the Japanese and American companies as initially it was one of the conditions for their products to enter the European Community’s markets and later as it has become the worldwide quality system norm and practices. Therefore, it was not ISO 9000 that had transformed the Japanese neither the American products to be of the best quality in the world. In Malaysia’s local organizations including the shipbuilding and ship repair industry, the general perceptions are that if they are of ISO 9000 certified, their products or services are of better quality. While ISO without doubt if being fully imple‐mented, since it has all the elements including Quality Planning, Quality Control, Quality Improvement and Continuous Improvement, etc., it will definitely make an organization to be an excellent one. But from some past experiences, num‐bers of organizations in Malaysia stressed the ISO 9000 implementation more on documentations or in simple words on papers it looks or seems to be less or without deficiency but in the real processes there were lots of deficiency even though the end product eventually managed to be delivered. In many local organizations ISO 9000 was only made impor‐tant while in the certification stage or during audits but after sometimes it had loose its steams.


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In some of these companies with or without ISO 9000 certified, even though they have the so called Quality Control/Quality Assurance departments, in reality in the production processes, they merely conducting Inspection, practically there was no Quality Control. Some of the projects undertaken partially did have the Quality Planning (.i.e. with the pro‐ject Quality Plan, Quality Standards, etc.) but some did not have it. Quality Improvement and Continuous Improvement generally were least or not implemented by most of the companies even though they are an important requirements un‐der ISO 9000. Therefore, the statistical method for Quality Control (SQC) or Process Control (SPC) which heavily used in manufacturing (especially multinationals) almost not deployed in many local organizations. No doubt that for number of new construction projects (i.e. shipbuilding) they were built to the Ship’s Classifications requirements and the product was subject to their approval from design, production till delivery but in reality along the processes the were a lot of deficiencies including mistakes, defects, scraps, reworks and etc. Mostly quality products only being granted at the delivery stage and not at beginning or work in process, but event with that in reality there were later on numbers of complaints from the clients when the products were put on services. In many shipbuilding projects there were a lot of losses in terms of time and costs due to the reworks and other defi‐ciencies. Many projects were not able to complete on time and within the budgeted costs or margins made were very small. Ship Classification doest not concern about cost or much about meeting the delivery time line. Reworks with more or repeat inspections perhaps would benefit more to ship classification which sometimes could be categorised as variation orders which automatically incurring more money to the shipyards. Therefore one cannot say that the shipyards have a good quality products or services even though it managed to produce one that certified by the ship classification society. A good organization should be able to provide product or services effectively that meeting the customer and the stake‐holder expectations and efficiently in the way be effective at minimum costs and resources incurred that would make it more profitable and competitive. Nevertheless to certify the above claims which some could merely a perceptions upon direct and indirect experienced with few companies and to have a wide coverage, a comprehensive study is to be conducted and more accurate data are to be collected from various shipyards in Malaysia and later on to be analysed and conclude as per the objectives and ex‐pected outcomes outlined in this paper above. Malaysian Shipbuilding, Ship Repairing and Offshore Construction: An Overview

Malaysia’s shipbuilding and ship repairing industry

Despite its stature as a maritime nation, it has been a matter of concern for the government and stakeholders in the local shipping industry that the level of national merchant shipping tonnage leaves much to be desired. There is a mismatch between growing demand for shipping services in the country and its increasing volume of mari‐time trade with the available capacity of local tonnage. According to the Malaysian Ship‐owners Association, an estimated 85 percent of the nation’s international trade is carried in whole or part by foreign‐flagged ships, causing a huge outflow of payments for foreign shipping ser‐vices. This situation inevitably puts the spotlight on the adequacy of the shipbuilding sector to provide the tonnage to support the nation’s ever‐growing trade volumes. The shipbuilding industry has been identified as a crucial sector to support the development of the country’s shipping sector and the growth of its trade. Given that Malaysia has set an ambitious target to achieve long‐term industrial competitiveness on a global basis through the transforma‐tion and innovation of its manufacturing and services sectors, industries such as shipbuilding must come to the fore to help the country to attain global competitiveness.


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The industry is also an important source of employment and provides a platform on which skills in various activi‐ties such as naval architecture, engineering, welding and fabrication, are developed. Additionally, it also has ex‐tensive linkages with many other industries such as steel, glass, logistics, storage, bulk‐breaking of goods, and services such as port services, financing, insurance and consultancy to the fore to help the country to attain global competitiveness. In the Third Industrial Master Plan 2006‐2020 (IMP3), the shipbuilding industry in Malaysia is identified as a stra‐tegic industry by the Malaysian government. However, local shipyards in general, have limited shipbuilding and ship repairing capabilities, mostly specialising in low‐value and small vessels. Local yards are confronted with many issues, including lack of qualified personnel, high operational costs, and face stiff competition from ship‐yards in countries such as Vietnam and Thailand that offer low labour costs. The number of shipyards in Malaysia with manufacturing licenses has grown over the years, but the industry in general is fragmented and the majority of the players are small shipyards which are labour‐intensive and operate on a small‐scale basis, building vessels mainly for the local market and for use in the shallow waters. Reputable local yards are capable of building and servicing vessels of considerable size. Some can build patrol vessels, OSVs, passenger vessels and leisure craft for the export market, producing reliable vessels at very com‐petitive costs. Large fabricators can build specialised vessels such as FPSO and provide high‐end services for the offshore oil and gas sector. However, local orders for larger and more sophisticated vessels are still placed with foreign shipyards which have the capacity and are technically more adept at building such vessels. This stems from their technical and capacity limitations to build big, sophisticated ocean going vessels. Labour‐intensive and inefficient shipbuilding methods and processes deployed at many local yards render them uncompetitive and inhibit the production of high quality vessels. At small yards, welding techniques and processes are still done manually or with semi‐automated machines. Launching of vessels using pressurised rubber rollers or steel pipes without a need to build dry dock, and slipways are widely used to lower costs. These prevent small local yards from undertaking more ambitious jobs and from expanding their business. Most local shipyards do not have the capacity to undertake the construction, repair and maintenance of large and technically challenging vessels. Due to the limitation of local yards to build and service bigger vessels, many local shipowners order ships from shipyards abroad and prefer their vessels to be repaired and maintained there. Many regional yards are now capable of offering products and services at highly competitive costs, hence posing a threat to Malaysian shipyards. Local shipyards have to improve the product and service offerings to convince ship owners that they are capable of building quality vessels and servicing them at competitive rates and fast turnaround time. The onus is on the yards to increase their efficiency and productivity and put in place well‐trained and skilled manpower to enhance their competitiveness and product/service offerings. As the shipbuilding industry is crucial to facilitating the growth of trade and economic development in Malaysia, it is essential that efforts are made to bolster the capacity and performance of the sector by way of learning from the successful experience of leading shipbuilding nations.


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Malaysia’s Offshore Construction

Petroleum is essentially the most important commodity in the world today. In almost all form of transportation, oil or petrol, derived from crude petroleum, is used to move people and the importance of petrol is seen with the establishment of offshore drilling structure fabricator and the supporting industries in Malaysia. The world’s pricing mechanism of petroleum is determined by Organization of the Petroleum Exporting Countries (OPEC) and is quantified by barrels of crude oil. At peak, price of crude oil is USD147.27 per barrel in July 2008 following concern of an impending missile test by a Middle East country, while 5 months later, following news of the collapse of various financial institutions in the US, price of crude oil fell to USD33.87 per barrel. As of August 2009, crude oil has stabilized at USD70 per barrel. As the price of crude oil slowly increases, in tandem with the recovering world economics, oil and gas companies are starting to accelerate their search for new oil and gas fields and in doing so, more offshore drilling structure are required to churn out petroleum. As of today, there are seven of such yards in Malaysia that is capable of fabricating offshore structure or under‐taking offshore fabrication namely Malaysia marine and Heavy Engineering (MMHE), Kencana HL, Sime Darby Engineering, Boustead Heavy Industries, OilFab, Ramunia Fabricators and Brooke Dockyard as listed in Table 2. This is added by the fact that more fabrication jobs totalling to RM4 Billion, would be offered by the end of 2009, thus spurning the growth of any seven of the local players (The business Times, 2009).

Table 2: List of major Malaysian shipbuilding, ship repairing and offshore constructors


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CONCLUSION AND RECOMMENDATIONS Realizing the important and benefits of quality as one of the organization’s tools towards less deficiency, cost reduc‐tion, meeting deadline, total customer satisfaction and ultimately greater competitiveness and the strategic of marine industries to Malaysia, it is recommended that further research on quality implementation to be conducted within Malay‐sian shipbuilding, ship repairing and offshore structure construction industries with the above objectives and expected outcomes that would benefit the academic fraternity in particular and the related industries in general.

REFERENCES Joseph. M. Juran (1998). How to think about Quality: The Juran Trilogy. Juran’s Quality Handbook, 5th Edition. McGraw‐Hill, USA. Frank M. Gryna (1998). Quality and Cost. Juran’s Quality Handbook, 5th Edition. McGraw‐Hill, USA. Donna C.S. Summers (2003). The Evolution of Quality. Quality, 3rd Edition, Prentice Hall, USA. Nazery Khalid (May, 2010). Full Speed Ahead! : The curious case of Malaysian shipbuilding industry. Feature/ Opinion, www. Baird Maritime.com. Offshore Construction in Malaysia. www.oppapers.com

http://www.oppapers.com


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Abstract

This paper presents the design and study of a stacked rectangular microstrip antenna with probe fed to enhance its gain and bandwidth for WiMAX applications. The stacked patch antenna consists of two layers. The optimized antenna which has one patch at the bottom and three patches at the top resonates at 3.5 GHz with a gain of 10.07 dB. It also ex‐hibits an impedance bandwidth of around 18.03% with 2:1 VSWR. The simulation was done by using 3D‐Electromagnetic modelling software, CST Microwave Studio version 2006B. Keywords: Stacked antenna, WiMAX, CST Microwave Studio Introduction With the rapid development in wireless technology, WiMAX (Worldwide Interoperability for Microwave Access) is the most promising that is able to support high‐speed wireless broadband applications with rather long reach, mobility, and roaming (Azaro et al., 2006 ). Recently, some antenna design for WiMAX have been proposed and studied in literatures (Yang, Chen and Yu, 2008, Hsueh et al., 2008, Roshanaei and Faraji‐Dana, 2007, Chen, Chang and Chang , 2007, Chen and Kao,2006). The advantages of microstrip antennas such as low weight, low cost, conformability and low profile (Balanis, 2005) offer a good choice for wireless applications. However, a single patch antenna has a low gain and a narrow bandwidth. Several methods have been proposed in the past to widen the bandwidth of the patch antenna. A common method for improving bandwidth performance is to add parasitic elements to the antenna structure [8‐20]. Stacking improves the characteristics of patch antenna such as gain, bandwidth, efficiency, input impedance, and reduces the phenomenon of cross polarization (Devaraj, Ajayan and Baiju, 2007). Probe fed stacked patch antennas have achieved wide attention over years due to its robust nature. It provides good isolation between feed network and radiating element, and due to direct contact with the radiator, dielectric misalign‐ment difficulties are reduced (Gupta and Gupta). Therefore stacked configuration with probe fed has been considered. In this paper, the bandwidth and gain enhancement of microstrip antenna with probe fed and parasitic patch was studied for WiMAX applications at 3.5 GHz. The 3.5 GHz frequency is the licensed band that has been accepted for WiMAX system in most countries. Up to 18.03% of impedance bandwidth for one bottom driven patch and three top parasitic patches were obtained. Due to its multiresonance property, the stacked can also operate at dual bands provided its dimensions are properly chosen. The design and optimization have been done using commercial modelling software, CST Microwave Stu‐

PERFORMANCE ANALYSIS OF WIDEBAND STACKED MICROSTRIP ANTENNA FOR WIMAX APPLICATION

SHAREEN ADLINA SHAMSUDDIN

Department of Marine Electrical and Electronics Technology Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur


Received: 1st December 2011, Revised: 15th December 2011, Accepted: 16th December 2011


Volume 2 (2) 2011 58

Antenna design The configuration of the stacked patch antenna is shown in Figure 1.

The stacked patch antenna consists of two layers. The lower patch is fed with a coaxial probe and top parasitic patches are electromagnetically coupled to the lower one. To achieve the broadest possible impedance response, a low permittivity microwave laminate of εr = 2.2 (RT Duroid 5880) in combination with dielectric foam are used. This combina‐tion has the simplest design procedure for stacked patch antenna (Rod Waterhouse, 2007 ). The thickness of h1 and h2 is chosen to be 1.575 mm and 5.8 mm. Calculation of patch dimensions are based on the transmission line model (Balanis, 2005) as given by equations below. The width of the microstrip patch antenna is equation (1) as:

The length and the width of the rectangular patch antenna from calculation are l = 28.06 mm and w = 33.88 mm re‐spectively. The parasitic elements with the same dimensions are placed on the upper substrate. These parameters and probe fed are then optimized to get desired results. The solver used for this simulation is a transient solver. It uses only one computational run for the simulation of a structure’s behaviour for a wide frequency range (CST Studio Suite, 2006 ).

Figure 1: The Stacked Patch Antenna


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Results and Discussion

The performance of stacked antenna was analyzed for several categories.

The Effect of Adding Parasitic Patches Figure 2 and 3 show the return loss, S11 and VSWR for four kinds of microstrip antenna. S11 and VSWR are critical parameters to determine the performance of antenna. S11 indicates the amount of signal being reflected and VSWR is basically a measure of the impedance mismatch between the transmitter and antenna (Besser and Gil‐more) . The simulation for single patch antenna gave bandwidth of about 2.77% at ‐10dB return loss or VSWR ≤ 2. To increase the impedance bandwidth, parasitic patch is added. Presence of a parasitic patch (upper patch) above the driven patch (lower patch) has two effects depending on the design (Sainati, 1996). Firstly, new resonant fre‐quency appears in S11 characteristics due to the parasitic patch. Secondly, the bandwidth and gain increase in proportion to the induced coupling between the patches. As evidenced, adding the parasitic patches enhance the bandwidth further up to 18.03% for one rectangular patch at the bottom and three patches on the top (1B3T).

Figure 2: Return loss for antennas

Figure 3: VSWR for antennas


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The gain performance is displayed in Figure 4. Gain of 6.340 dB was achieved by single patch antenna. However, the gain keep increases as the parasitic patches were added where it gave 10.07 dB for 1B3T. Table 1 shows the simulated results for the antenna performance.

From Table 1, it can be observed that 1B3T gives the minimum value of S11 which indicates more signal being transmitted and less signal being reflected. The reflected signal is due to the impedance mismatch. Hence, S11 is a parameter similar to VSWR to indicate impedance matching. The higher the VSWR, the greater the mismatch. The minimum VSWR which corrresponds to a perfect match is unity. In practical applications, a VSWR of 2 is accept‐able since this corresponds to a S11 of ‐10 dB. The impedance bandwidth can be measured from these two condi‐tions. Thus, it can be concluded that the four antennas have operating band with the desired bandwidth for Wi‐MAX applications. WiMAX protocol required the frequency bandwidth of 50 to 100 MHz at each of its designated frequency band (Roshanaei and Faraji‐Dana, 2007).

Figure 4: Gain for antennas

Table 1: Simulated Results


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The Effect of Substrate Thickness

The thickness of each layer also plays an important role in achieving the overall bandwidth. Traditional concepts of antenna design would suggest that a thicker substrate would yield a larger bandwidth. The observation was made for 1B3T antenna.

Figure 5 and 6 illustrate the effect of height for primary patch substrate, h1 on the S11 and VSWR while keeping the upper substrate h2 = 5.8 mm. It is observed that as h1 increases from 0.508 mm to 3.175 mm, the bandwidth of the antenna increases from 5.44% up to 25.47% due to the total height of the antenna increase. However, the primary patch substrate must be sufficiently thick to maximize the bandwidth, but not overly so, which would result in a driven patch that is excessively inductive (Rod Waterhouse, 2007). The inductive element will reduce the quality factor, Q, hence reduce the bandwidth. The relationship of Q and bandwidth is given by equation be‐low.

Figure 5: Return loss for varying h1

Figure 6: VSWR for varying h1


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As the thickness of h1 increases, gain of the antenna decreases as shown in Table 2. Gain degrade from 10.11 dB for h1 = 0.508 mm to 9.661 dB for h1 = 3.175 mm. However, the impedance bandwidth increases with the in‐crease of h1. Thickness h1 = 1.575 mm has the best performance since it gives minimum S11 and VSWR, also high gain of 10.07 dB. Variations of h1 are based on the standard thickness from datasheet Rogers 5870/5880.

The thickness of the upper layer substrate, h2 primarily governs the level of mutual coupling. In general, mutual coupling is primarily attributed to the fields that exist along the air dielectric interface (Balanis, 2005). Mutual coupling affects input impedance, radiation pattern and gain of the antenna. The thicker this layer is made, the smaller the loop in the impedance locus becomes as illustrated in Figure 7. The thickness of h2 depends upon the thickness of h1. The greater h1 leaves less freedom for h2 (Rod Waterhouse, 2007). Table 3 lists the performance parameters related to the varying of h2 while keeping h1 = 1.575 mm.

Table 2: Variation of Bandwidth and Gain of 1B3T antenna with h1

Figure 7: The Smith Chart for varying h2


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From Table 3, it can be observed that the thickness h2 is inversely proportional to the gain. As the thickness h2 increases, the gain decreases. However, the thickness h2 will enhance the bandwidth but to certain point, the bandwidth start to degrade. It can be concluded that varying h2 is helpful for optimizing gain and bandwidth over frequency.

The Effect of relative permittivity, εr

To see the effect of εr to the performance of antenna, the antenna was designed with εr1 = εr 2 = 2.2 (RT Duroid 5880) and h1 = h2 = 1.575 mm. The S11 is given by Figure 8. It can be seen that both antennas, 1B1T and 1B3T, gave a wider bandwidth. The details parameters are listed in Table 4.

Table 3: Variation of Bandwidth and Gain of 1B3T antenna with h2

Figure 8: Return loss versus frequency


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From the Table 4, it can be observed that the gain and impedance bandwidth increase due to the additional of parasitic patch. However, the bandwidth is not wider compared to Rogers and foam formation.

Dual frequency

Stacked patch antenna is very useful to enhance the bandwidth or to create a dual‐band efficient patch antenna due to its multi resonance property. This is illustrated in Figure 9 for S11 versus frequency.

It is clear that despite its simple structure, the 1B2T antenna can operate at 3.5 GHz and 2 GHz frequency bands simultaneously. Similarly, 1B1T antenna also can operate at 3.5 GHz and 6 GHz frequency bands simultaneously. The gain for 1B2T antenna is 10.36 dB and 8.255 dB for 1B1T antenna

Table 4: Simulation Results for RT Duroid 5880 Substrate

Figure 9: Return loss of stacked antennas


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Conclusions

The performances of the rectangular stacked microstrip antenna for WiMAX applications at 3.5 GHz are studied. 1B3T antenna with low permittivity microwave laminate in combination with dielectric foam enhanced gain of 10.07 dB at the resonant frequency and 18.03% bandwidth has been achieved which are acceptable for WiMAX applications. References R. Azaro; G. Boato; M. Donelli; A. Massa,; E. Zeni (2006). Design of a Prefractal Monopolar Antenna for 3.4‐3.6 GHz Wi‐Max Band Portable Devices. IEEE Antennas and Wireless Propagation Letters, Vol. 5, pp. 116‐119. K.C. Yang, W.S. Chen, and Y.H. Yu (2008). Design of a WiMAX T‐type monopole antenna with asymmetrical ground plane. Antennas and propagation Society International Symposium, 2008, AP‐S 2008, IEEE, pp. 1‐4. T.M. Hsueh, H.T. Hsu, H.T. Chou, and K.L. Hung (2008). Dual Band Omni‐Directional Planar Antenna for WiMAX Appli‐cations. Antennas and Propagation Society International Symposium, 2008, AP‐S 2008, IEEE, pp. 1‐4. M.Roshanaei; R. Faraji‐Dana (2007). A New Quad‐Band CPW‐Fed Stacked Antenna for Wireless LAN Applications. Elec‐tromag. in Advanced Applications, 2007. ICEAA 2007, pp. 535‐538. W.S. Chen, Y.C. Chang, and F.S. Chang (2007). Novel Design of Printed Monopole Antenna for WiMAX Application. Microwave and Opt. Tech. Letters 49, pp. 1806‐1809. W.S. Chen and B.H. Kao (2006). The Design of Printed Rectangular Slot Antenna with a Small Isosceles Triangle Slot for WiMAX Application. Microwave and Opt. Tech. Letters 48, pp. 1821‐1824.

C.A. Balanis (2005). Antenna Theory: Analysis and Design. 3rd Edition, John Wiley and Sons, Inc, pp. 811‐872 Medeiros, C.; Costa, J.R.; Fernandes, C.A. (2008). MEMS Reconfigurable Stacked Antenna for WLAN Applications. An‐tennas and Propagation Society International Symposium, 2008, pp. 1‐4. Nasimuddin; Z.N. Chen (2008). Wideband Microstrip Antennas with Sandwich Substrate. IET Microw. Antennas Propag., 2008, Vol. 2, No. 6, pp. 538‐546. Liqiang Hao; Jungang Miao; Xin Zhao (2007). A Method to Improve the Performance of the Stacked Circularly Polar‐ized Microstrip Antenna. International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wire‐less Communications, 2007, pp. 519‐522. Noro, T.; Kazama, Y.; Takahashi, M.; Ito, K. (2007). A Study on the Mechanism of Wideband Characteristics for Single‐Fed Stacked Circularly polarization Patch Antenna”, IEEE Antennas and Propagation Society International Symposium, 2007, pp. 733‐736. Yang, C.F.; Tzou, W.C.; Tsai, J.H.; Chen, H.M., Lin, Y.F. (2007). Enhance Antenna Bandwidth by Using High Permittivity Ceramic and FR4 Stacked Structure. IEEE Antennas and Propagation Society International Symposium, 2007, pp. 1012‐1015.


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Rajo‐Iglesias, E.; Quevedo‐Teruel, O.; Inclan‐Sanchez, L. (2007). Study of Mutual Coupling Reduction in Single and Stacked Multilayer Patch Antennas by using planar EBG structures. IEEE Antennas and Propagation Society International Symposium, 2007, pp. 393‐396. Nasimuddin; Essele, K.P. (2007). High‐Gain Wideband circularly Polarized Stacked Microstrip Antennas with Single Microstrip Feeds and Short Horns. Antennas and Propagation International Symposium, 2007 IEEE 9‐15 June 2007, pp. 737‐740. Ang, I.; Ban Leong Ooi (2005). A Broad Band Stacked Microstrip Patch Antenna. Microwave Conference Proceedings, 2005. APMC 2005. Asia‐Pacific Conference Proceedings, Vol. 2, pp. 2‐3. Nishiyama, E.; Aikawa, M. (2004). Wide‐band and High‐gain Microstrip Antenna with Thick Parasitic Patch Substrate. IEEE Antennas and Propagation Society International Symposium, 2004, V0l. 1, pp. 273‐276. Wei Wang; Shun‐Shi Zhong; Xian‐Ling Liang (2004). A Dual‐Polarized Stacked Microstrip Antenna Subarray for X‐Band SAR Application”, IEEE Antennas and Propagation Society International Symposium, 2004, Vol. 2, pp. 1603‐1606. Kyungjin Oh; Bongjun Kim; Jaehoon Choi (2004). Design of Dual and Wide Band Aperture Stacked Antenna with Dou‐ble‐Sided Notches. IEEE Antennas and Propagation Society International Symposium, 2004, Vol. 3, pp. 3091‐3094. Nishiyama, E; Aikawa, M; Egashira, S. (2003). Three‐Element Stacked Microstrip Antenna with Wide‐Band and High‐Gain Performances. IEEE Antennas and Propagation Society International Symposium, 2003, Vol. 2, pp. 900‐903. Bulja, S.; Mirshekar‐Syahkal, D. (2003). Very Low‐Profile Multilayer Broadband Microstrip Antenna. Antennas and Propagation, 2003 (ICAP 2003), Twelfth International Conference on Conf. Publ. No. 491), Vol. 2, 2003, pp. 481‐484. V. Devaraj; K.K. Ajayan; M.R. Baiju (2007). A Novel Optimization for a Stacked Patch Antenna”, Proceedings of Asia‐Pacific Microwave Conference, 2007, APMC 2007, pp. 1‐4. Gupta, V.B.; Gupta, N. Gain and Bandwidth Enhancement in Compact Microstrip Antenna. www.ursi.org/Proceedings/ProcGA05/pdf/BCP.6(0753).pdf

Rod Waterhouse (2007). Printed Antennas for Wireless Communications. John Wiley and Sons, Ltd., pp. 56‐67. CST Studio Suite ™ 2006, pp. 3‐4 Les Besser, Rowan Gilmore, Practical RF Circuit Design for Modern Wireless System, Artech House, Boston, London, pp. 61‐63.

Sainati, R.A. (1996). CAD of microstrip Antennas for Wireless Applications, Artech House Inc., Norwood, MA.


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Abstarct The function of plurality exists in both Malay and English language. However, there are significant differences in the formation of plural forms between both languages. Despite learning the English language for eleven consecutive years at the primary and secondary levels, students are still unable to apply the correct structure of plurality in English language. A study conducted on 40 semester one students of a local higher learning institution shows that majority of students under‐stand the function of plurality, but found it difficult to write the correct spelling of the plural forms. This is due to the vari‐ous spelling rules of the plural inflections in the English language. For example, students have to know when to use the plural inflection (i.e. –s as in books, ‐es as in busses, ‐ies as in stories). These spelling rules are some of the constraints face by the Malay students since there are less complicated rules in the formation of plurality in the Malay language. Among the tools used for measuring the students’ competency in plural inflection are cloze‐tests and essays. Results show that errors regarding plural inflection in students’ written tasks are affected by the differences of plural inflections between Malay and English language. Keywords: Plurarity, affixes, contrastive analysis Introduction Generally, Malaysian children were introduced to this language as early as four or five years old, at their pre‐school level. This teaching and learning process gradually continues from pre‐school to primary and secondary school. The dura‐tion of exposure towards English language in classroom setting would be approximately 11 years. Although English lan‐guage has been given much respect and attention, there are still learners being underachievers and not proficient in the language at the end of their secondary school level. In order to be fully proficient in a language, one must master all four skills‐ listening, speaking, reading and writing. Unfortunately, in the Malaysian context, more emphasis is given to reading and writing skills at the early stage of learning English language. The students’ proficiency in English language is measured by written examinations, giving less focus on oral performances. Hence, the teaching and learning process of English language in classrooms revolves around writing performances of the students. By understanding this situation, we will definitely expect the students to be good in their writing system.

AN ANALYSIS ON THE PLURAL INFLECTIONS OF ENGLISH LANGUAGE AMONG MALAY STUDENTS

SARAH NADIAH BINTI RASHIDI

Department of General Studies Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur


Received: 21st April 2011, Revised: 24th May 2011, Accepted: 21st November 2011


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According to Lim Ho Peng (1976), Azimah (1998), Khan (2005), Vahdatinejad (2008) there is a gradual decline in the standard of English language in Malaysia. There are still students who fail to understand the most basic rules of English language structure, such as plurality. What are the factors affecting these students’ difficulties in using one of the simplest rules like plural form? This paper will investigate the regular occurrences of errors in the use of plural inflections which are identified in students’ essay by contrasting the plural form of English and Malay language. Fries (1945), Lado (1957) and Van Els (1984) agreed that different grammatical structure between languages is a pos‐sible factor of students’ incompetency in the targeted language. Hence, the hypothesis of this study is Malay students find it difficult to understand and use English language plural inflections because there are no plural inflections in the Malay language. Aims of Research

I. To identify and explain students’ error regarding plural inflection II. To identify the differences & similarities of plural inflections between Malay & English language. III. To measure and determine whether the differences of plural inflections formation between Malay and Eng‐

lish language contribute to the errors in students’ writing. In order to achieve the aims of this study, the researcher has to identify, analyzed and explained the errors made by students regarding plural inflections. These steps can be done by first contrasting the similarities and differences of plural inflection between Malay and English language. Then, the researcher must measure and determine whether the differ‐ences of plural inflections formation between Malay & English language contribute to the errors in students’ writing using the assessment tools which are cloze‐tests and essays. The results from previous studies related to this subject matter and the definition of plural inflection will be pre‐sented in the next chapter. Literature Review

I. Contrastive Analysis Contrastive analysis is an inductive investigative approach based on the distinctive elements in a language. In this paper; the researcher focuses on the analysis of morphemes which carries grammatical meaning. Some researchers believed that when similarities & differences between L1 & L2 were identified, pedagogy could be more effective. This statement is developed from the master mind of contrastive analysis, Lado (1957) where he stated “those elements that are similar to the learners’ native language will be simple for him, but those that are different will be difficult.” Hence, this study is significant since the aspect of plurality is being analyzed in terms of both languages. Lado’s state‐ment supports this paper’s hypothesis that Malay students find it difficult to understand and use English language plural inflections because there are no plural inflections in the Malay language. Hashimah, Norsimah, Kesumawati (2008) in their study of grammatical structures agreed that different construc‐tion of plural forms in Malay and English language contributes to the difficulty of acquiring the language II. Inflection Inflection is a change in the form of words that indicate certain grammatical relationships such as number, gen‐der and tense. Inflection morphemes are those prefixes (combination of letters that comes in the beginning of a word; e.g. unclear, restart, misbehave) and suffixes (combination of letters that comes at the end of the word; e.g. climbing, washed, writes, tables) that perform a grammatical function. (Lehmann, Covell)


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III. English number morphemes Source from Stockwell, Stageberg, Gleason, Quirk and Greenbaum, Eckersley & Eckersley, Frank, Jackson, Covell, Web‐ster Unabridged Dictionary. English has two forms of number: singular and plural. Singular indicates only one while plural indicates two or more. In this paper, the researcher covers only plurality on NOUN (words such as ‘table’, ‘love’, ‘calendar’,’ child’ which used to refer to a person, thing or emotion status. In English language, the class NOUN is linked with an inflec‐tional category NUMBER. The plural suffix /–s/ is added to the base form to convert it from singular to plural (see table below). However, not all words can be made to plural just by adding /‐s/. (see table below) Due to this various rules of forming plural words, second language users of English language often confused and committed errors in writing.

Methodology

In order to achieve the aims of this study, the researcher implemented 3 assessment tools to collect the data; Cloze‐tests, Essays and Fill in the blank. The first methodology implemented by the researchers was the use of Cloze Test. The function of the Cloze‐test was to measure and determine the students’ understanding of plural inflections in English lan‐guage. The researcher used two sets of Cloze‐test to gather a more genuine data regarding plural inflection. There were ten questions in each Cloze‐test and students have to answer to a total of twenty Cloze‐test questions. Each Cloze‐test con‐sisted of various morphological & syntactical structures. The researcher included various structures as she does not wish for her respondents to be aware that this was a test on plural form. However, once the Cloze‐test is collected, analysis is made only on PLURAL INFLECTIONS. The second approach implemented by the researcher was essay. Only six essays were taken to be analyzed. These essays were chosen based on students’ proficiency levels. Three essays representing the low proficiency and three essays from higher proficiency students. All essays were about the same topic‐ ‘Is television a bad influence?’ and they had been marked earlier; Instead of focusing on all grammatical errors, analysis was made only on Plural Inflections. The third meth‐odology applied by the researcher is Fill in the blank. There are 10 questions consisting of ten singular nouns. Students were to convert these singular words into their plural forms.

Singular Plural

Table Tables

Calculator Calculators

Singular Plural

Child Children

Mouse Mice


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In this study, a total of 40 semester one students were selected as the sample of the study. They were 20 lower profi‐ciency students and 20 higher proficiency students of a local semi‐private higher learning institution in Malaysia. The stu‐dents’ level of proficiency was pre‐determined by an English Placement Test which is a compulsory assessment of the in‐stitution. In this study, students who passed the English Placement Test are categorized as higher proficiency while those who failed are categorized as lower proficiency students. The reason for selecting samples of different proficiency is to consider that despite the plural inflections differences between the two languages, students are still able to grasp the idea of plurality in English language. It is believed that stu‐dents from the higher proficiency group are able to score better in their Cloze‐test, Essays and Fill in the blank tasks. Findings In this chapter, the data is collected by initially selecting the sample and then distributing the instruments which are Cloze‐test, Essays and Fill in the blank to the sample. The next step is assessing the data collected and turns the data into percentages which is then known as the findings. Then, the findings are discussed by comparing the structures of plural inflections of the Malay and English language in the latter part of this chapter. In Cloze‐test 1, there are 4 questions on plural inflections; Question 1, 4, 6 and 9.

Based on the chart above, only 3 out of 20 or 15% of the higher proficiency students committed errors in Question 1. Surprisingly, all of the lower proficiency students answered Question 1 correctly. As for Question 4, majority of the stu‐dents of the higher and lower proficiency answered the question incorrectly. The correct answer for Question 4 is D. wives. 30 out of 40 or 75% of students mistakenly responded B. wifes. As for Question 6, 11 or 28% of students from each proficiency level respectively answered B. beachs instead of the correct answer C. beaches. For the final question in Cloze‐test 1, only 6 out of 20 or 30% of higher proficiency students answered Question 9 wrongly. On the other hand, 14 out of 20 or 70% of lower proficiency students mistakenly answered Question 9. Most of the students who gave the wrong an‐swer cirlced B. childs and D. childrens whereas the correct answer should be C. children.

Chart 1: Errors on plural inflection in Cloze‐test 1


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The correct answer for Question 3, 5 and 7 are mice, wolves and boxes. 40% of higher proficiency students got the wrong answers for all three questions with majority of them circled ‘mouses’, ‘wolfes’ and ‘boxs’. Significant percentages were identified as there were more lower proficiency students committed errors for all three questions Below are the frequent errors made by students in the 6 essays collected by the researcher.

Based on Table 2 above, the words in bold are the errors made by students in their essay. From the table, it is found that students included the suffix /–s/ in the words‐ childrens, heros and womans. However, for words like actress and dress, the students overlooked the suffix /–s/. The factors of these errors will be discussed in the latter part of this chap‐ter.

Chart 2: Errors on plural inflections in Cloze‐test 2

Table 2: Frequent errors made by students in essays


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There are 10 words that the respondents need answer in this Fill in the blank task. It is found that the higher profi‐ciency students perform better in this task compared to the Cloze‐test as they only answer Question 2, 6 and 9 incorrectly. In contrast, the lower proficiency students got the wrong answers for all questions, except for question number 8.

Chart 3: Errors on plural inflections in Fill in the blank task

Table 1: Comparison of errors made by students for Fill in the blank task


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Table 1 shows the list of singular nouns that students need to change into their plural forms. In this paper, the researcher highlights Question 2, 6 and 9 for those were the questions that carried high percentages of error in the usage of plural inflections. As stated in Table 2, it is found that majority of students from both proficiency levels over‐generalize the use of suffix –s in all words. It is shown that most students who committed errors in Question 2, 6 and 9 include the suffix –s for all the words. For example:

The over‐generalization of the suffix –s and other factors contributing to the errors made by students regarding plural inflections will be discussed in the next chapter. Discussion In this chapter, the discussion is divided into two parts where it begins by contrasting the plural form of the malay and English language and ends by determining whether the result of the contrastive analysis between the two languages have affected the errors made by students. Unlike the Malay language, the plural formation of words in the English language is much more complicated because there are many spelling rules. Malaysian students are exposed to idea that the suffix –s is needed to indicate plurality. Less are they aware of the other spelling rules of plural inflections in the English language such as:

Table 3: Common errors made by students

Table 4: Spelling rules for formation of plural forms in English language


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As seen in Table 4, there are a lot of complicated and confusing spelling rules to indicate plurality in English language. How can we blame the students for not being able to understand the spelling rules? Do they have to memorize the rules in order to be proficient in the language? These are the questions that have to be cater in order for educators to apply a better lesson for their students regarding plural structures. Plural inflections become more complicated when it is influ‐enced by loan words. Only through exposure will the students be able to grasp the idea of plurality in the English lan‐guage.


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From the Cloze‐test and Fill in the blank tasks, the students were clearly aware of the usage of plurality. The only drawback they faced was the over‐generalization of the suffix /‐s/ for all words, as seen in Table 3. The students from ei‐ther higher or lower proficiency level are confounded with the complex plural inflections because the formation of plural words is easier in the Malay language. It can be seen in Table 5 below.

In the Malay language, the common method to show plurality is by reduplication. Plurality is called ‘kata ganda’ which simply mean duplicate. Plural inflections exist in three common suffixes‐ /‐s/, /‐es/ and /‐ies/ for English language. Stu‐dents either spell it right or got the answer wrong for the plural words. However, in the Malay language, things are much simpler as students are needed to just reduplicate the words in order to make it plural. Below is the comparison of the singular word mouse:

In English language, students have no option rather than to know that the suffix /‐es/ must be added to words that end with /‐f/. If students spell it as shelfs, it would be wrong. The malay language is easier compared to the English lan‐guage since students have option to either duplicate the word ‘rak’ using the symbol (‐) or to insert cardinal or ordinal words before the word ‘rak’ in order to show plurality. If cardinal or ordinal words are used, the word ‘rak’ will remain face no changes at all. E.g. some shelvesà beberapa rak. To be safe, most students will apply the use of reduplication. Despite all the differences in the formation of plurality between both languages, there are similarities identified by the researcher. In both languages, plurality is indicated by cardinal like all (semua), some (sebahagian/beberapa). For ex‐ample:

Table 5: Rules for formation of plural forms in Malay language

Table 6: Comparison between English and Malay language plural forms


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Conclusion and Recommendations This study has found that there are differences and similarities regarding the formation of plural forms between Ma‐lay and English language. In responding to the aim of this study, it is believed that the differences of plural inflections for‐mation between those languages contribute to the errors in students’ writing. Based on the data collected, it is found that the respondents understand the when and why should we use the plural form. The errors occurred not because the re‐spondents failed to grasp the idea of plurality, but they are confused with the complicated rules of plural inflections in the English language. Hence, this study is significant for it creates awareness to the readers on the importance of knowing the differences between two language structures. It has an impact to the teaching and learning environment as it serves as a guideline for educators. Now, the educators will have the opportunity to acknowledge the areas tat students are weak in. with the re‐sults from this study, educators are able to prepare better lesson plans to cater the students’ difficulties. Teachers can provide better explanation for grammatical structure like the plural inflection in classroom by considering comparing rules of both languages. As for future study, consider of incorporating more sample to measure the students’ authentic understanding on the usage of plural inflections. It is also recommended that in the future study, emphasis should also be given to other aspects of plurality such as the loan words rather than just focusing on the inflectons /‐s/, /‐es/ and /‐ies/. REFERENCES Nor Hashimah Jalaluddin, Norsimah Mat Awal, Kesumawati Abu Bakar (2008) The Mastery of English Language among Lower Secondary School Students in Malaysia: A Linguistic Analysis. European Journal of Social Sciences, Vol 7, 1‐14 Asmah Hj. Omar. (1986). Nahu Mutakhir Melayu. Kuala Lumpur: Dewan Bahasa dan Pustaka Khazriyati Salehuddin, Tan Kim Hua & Marlyna Maros. (2006). "Definiteness and Indefiniteness: A Contrastive Analysis of the Use of Determiners between the Malay Language and English". GEMA Online Journal of Language Studies. Volume 6 (1) Nik Safiah Karim dan lain‐lain. 2001. Tatabahasa Dewan Jilid 2: Perkataan. Kuala Lumpur, Dewan Bahasa dan Pustaka.


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Abstract

This research was conducted to identify the energy of wave induced by boats at the estuary area. The location of the study was at the estuary of Sepetang River, Perak. In this study the water level logger was used to measure the parameters and deployed over one tidal cycle. At normal condition, it was observed that the energy produced naturally is low‐energy, but the technology available on the boat has contributed to the production high‐energy at the area. The results have shown that the energy level produced from Class A fishing boat was higher than Class B fishing boat at a constant speed. Hence, there is a strong relationship between wave height and energy level created by the boat as wake. It is hope that the find‐ing will provide useful information to the appropriate authority and policy maker and can be a guideline in creating a suit‐able policy and regulation. That could minimize the impact to the coastal environment in the future. Keywords: Energy level, estuary, boat Introduction

The aim of this study is to identify the difference of energy level induced by class A and class B fishing boats. To

achieve this aim, the following objectives will be established. First is to identify the energy level of wave induced by boats at the estuary. This followed by estimating bottom shear stress of mudflat induced by wave of boat, to investigate the relationship between depth and bottom shear stress and lastly to determine the relationship between wave height and energy level. An estuary is a semi‐enclosed coastal body of water with one or more rivers or streams flowing into it, and with a free connection to the open sea. Estuaries are thus subject to both marine influences, such as tides, waves, and the influx of saline water and riverine influences, such as flows of fresh water and sediment.

An example of Malaysia’s estuary is Kuala Sepetang which is a coastal town located in Perak, Malaysia. The town was formerly known as Port Weld. The site is also well known for its mangrove swamp reserve park. It is a thriving fishing vil‐lage, and the main jumping‐off point to the river mouth community which is a fishing community at the river mouth, which specializes in fish breeding in cages.

Human interference in hydraulic systems is often necessary to maintain and extend economic activities related to

ports and associated navigation channels. In many situations engineering structures are required to stabilize the shoreline, shoals and inlets in order to reduce sedimentation, to prevent or reduce erosion, or to increase the channel depth to allow larger vessels entering the harbour basin.


STUDY ON HIGH ENERGY EVENT INDUCED BY BOATS AT SEPETANG RIVER

NORAZLINA ABDUL NASIR

Malaysian Institute of Marine Engineering Technology University Kuala Lumpur

Received: 1st December 2011, Revised: 22nd December 2011, Accepted: 22nd December 2011


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Coastal protection against floods and navigability are the most basic problems in many estuaries in the world. Sedi‐mentation problems generally occur at locations where the sediment transporting capacity of the hydraulic system is re‐duced due to the decrease of the steady (currents) and oscillatory (waves) flow velocities and related turbulent motions (Van Rijn, 2004). An example of sediment pollution in Malaysia is the estuary of Sungai Johor where the pollution became critical due to sand dredging process. The compilation of sand was detected at the upstream at Kota Tinggi (Khairi, 2008). The deposition of sediment may produce new land and enhance existing land use for various purposes. Erosion creates sediment that makes a big damage to agriculture land by reducing the fertility and productivity of soil. In addition, the sediment influences several industrial and manufacturing.

Aim

This study involved collecting data from water level logger that was used to measure the parameters at the estuary as well as the wave characteristic. This data will identify the wave energy that was induced by boat at the study area. The data was also used to determine the bottom shear stress at the mudflat of the shallow water affected by the wave.

Literature Review

1. Sedimentation problems Sedimentation problems are most often associated with human interference in the physical system such as the con‐

struction of artificial structures or the dredging of sediment from the bed to increase the flow depth or width. However, sedimentation (as well as erosion) also is a basic phenomenon of nature dealing with loose sediments within the trans‐porting cycle from source to sink locations. Natural sedimentation areas are known as shoals, flats, banks, sheets, bars, etc. Human interference in these natural sedimentation areas will always lead to relatively large maintenance cost and should therefore be avoided as much as possible. Figure 1 is an example of man‐made arrangement structure at the river.

Figure 1: Examples of Man‐Made Structures in River, Estuary and Coastal Systems (Van Rijn, 2004)


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2. Wave generation

Wave motion is a disturbance that moves from place to place in some medium, carrying energy with it. Probably the

most familiar example of wave motion is the action of water waves. A boat at rest on the ocean moves up and down as water waves pass beneath it. The waves appear to be moving toward the shore. But the water particles that make up the wave are actually moving in a vertical direction. The boat itself does not move toward the shore or, if it does, it's at a much slower rate than that of the water waves themselves

The energy carried by a water wave is obvious to anyone who has watched a wave hit the shore. Even small waves have enough energy to move bits of sand. Much larger waves can, of course, tear apart the shore and wash away homes. There are two types of wave motion which are transverse and longitudinal (Kamphuis, 2000). A transverse wave is one that causes the particles of the surrounding medium to vibrate in a direction at right angles to the direction of the wave. A water wave is an example of a transverse wave. As water particles move up and down, the water wave itself appears to move to the right or left. Methodology

Water level logger was used to collect the parameters of the estuary and the wave characteristic. The parameters recorded include depth, pressure and water temperature. Wave gauges were deployed during low tide and the reading will be obtained during high tide. The data of water height was recorded at one second intervals. In addition, the calcula‐tion of wave energy (E) was done using the formula used by Kamphuis (2000). Where ρ is mass density of water in unit of kilogram per cubic meter, g is acceleration by gravity in meter per second squared. H is the significant wave height in me‐ter and a is an amplitude in meter.

The calculation of the bottom shear stress using the following formula was used by to Carper and Bachman (1986); Hamilton and Mitchell (1996); Bailey and Hamilton (1997) in their study in order to determine effective fetches and theo‐retical bottom shear stress at the sediment from the previous study. Where, τ is the bottom shear stress in unit Nm‐2, H is wave height (meter), ρ is mass density of water (kg/m3), T is wave period in second, k is wave number, h is depth of water in unit meter and lastly v is kinematics viscosity of water in cubic meter per second.


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From Figure 2 below, the energy level from Class A boat was higher than Class B fishing vessel. It was observed that the higher or lower energy level depended on the speed of the boats. Boats with maximum speed and minimum capacity will produce large energy, which has the characteristics such as large wave height, small wave period and short wave length. Figure 2 (a) is the result at the six meter from the river bank. The energy produce was large than Figure 2 (b) and 2 (c) due to the wave velocity and period taken near to river bank.

Figure 2: Energy level from Class A and Class B fishing boats


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At a similar speed of 4.4 knots both of boats A and B produced and energy of 0.6 and 0.4 Joule. Near the river bank, the highest energy produced from boat A was 1.04 Joule and boat B was 0.44 Joule. At a speed 4.4 knots both boat pro‐duced the same energy, i.e 0.30 Joule. As a result, the energy level produced from boat A was higher than boat B at a con‐stant speed 4.4 knots. The bottom shear stress at six meters from the river bank at a speed of 4 knots is 4E‐10 Nm‐2 for boat B and lower for boat A. The higher shear stress recorded at this point is 1.4E‐9 Nm‐2 for boat A and 8E‐10 Nm‐2 for boat B. At the position of three meters from the river bank and a speed of 4 knots, boat B produce a BSS of 5E‐10 Nm‐2 and lower for boat A is. The higher value of BSS is 1.4E‐9 for boat A and 5E‐10 Nm‐2 for boat B. Near the riverbank with a speed of 4 knot, BSS produced by boat B is 4E‐10 Nm‐2 and boat A is below then 1E‐10 Nm‐2. The higher value of BSS is 9E‐10 Nm‐2 for boat B and 4E‐10 Nm‐2 for boat A.

Consequently the higher bottom shear stress is produced by boat B compared to boat A at a constant speed of 4 knots as show in Figure 3. Waves that produced high energy level did not necessarily produced large shear stress. On the other hand, bottom shear stress value depended on the water depth, while the energy value depended on the wave char‐acteristics.

Figure 4 shows there have a strong relationship between independent and dependent variable exists. The correlation

coefficient is near to positive 1. The trend of regression line slope is upward and to the right. Value of the energy level was increase due to the wave height. Wave that produces the high of wave height was creating the high energy level. Accord‐ing to Sorensen (1930), at shallow water, the bottom condition rough and boundary layer is practically always rough tur‐bulent. Wave energy dissipation will occur due to the turbulent motion and resulting bottom shear stress in this boundary layer as well as by viscous dissipation outside the boundary layer. The finding in this study show wave that produces a high energy level does not necessarily produces large shear stress.

Figure 3: Shear Stress from Class A and Class B fishing boats

Figure 4: The relationship between wave height and energy


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Conclusion

In conclusion, the energy level that induced by boats at the estuary of Sepetang River was depended on the speed of the boats. An analysis of the result found that, the higher value of the wave height will create the smaller wave length and produced a high value of energy; meanwhile, the difference in speed between Class A and Class B boats depended on the capacity of their cargo. This trend was due to the characteristics of the river such as the width and morphology of the area. Nevertheless, the value of bottom shear stress induced by boats was significantly caused by the depth of water. In‐creasing in water depth will create smaller value of shear stress and vice versa. Any mudflat changes at the shallow water area will demonstrate the strength of wave energy effect. Waves move energy at far distance and water works as the me‐dium through which kinetic energy or energy in motion. On the other hand, the number of samples that were collected should be increased to get a use accurate result for the next study.

Recommendations

In future, this study can be further improved in order to determine the relationship between sediment soil strength and shear stress to measure the erosion. The effect of wave induced by boats that has been calculated in this study can be compared with the next study at a different area. More comparisons can be made between two or three classes of boats with constant speed and capacity in order to obtain a more reliable result.

References Kamphuis, J.William. (2000). Introduction to Coastal Engineering and Management. Advance Series on Ocean Engi‐neering. Volume 16. Queen’s University, Canada. World Scientific Publishing Co. Pte. Ltd.

Mohd Shah Khairi Mohd Suhaimi (2004). Identification of Sediment Pollution Source in Sungai Johor Estuary. Faculty

of Civil Engineering. University Teknologi Malaysia. Carper, G.L and R.W. Bachmann (1986). Wind resuspension of sediments in a prairie lake. Canadian Journal of Fisher‐

ies and Aquatic Sciences. Vol. 41. NRC Research press. 1763‐1767. Leo C. Van Rijn (2004). Estuarine and coastal sedimentation problems. Proceedings of the Ninth International Sympo‐

sium on River Sedimentation. Delft Hydraulics and University of Utrecht, The Netherlands. Kamaruzzaman BY, Ong MC, Ridwan H and Jalal KCA, (2008) Sesonal Surface Sediment Characteristic of the Kuala Se‐

petang River, Taiping, Perak. Sains Malaysiana, Vol 37 (2) : International Islamic University Malaysia. 143‐147. Yunus A. Cengel and John M. Cimbala (2006). Fluid mechanics fundamentals and applications. McGraw.Hill Interna‐

tional Edition. R. Verney, J.Deloffre, J.C. Burn‐Cottan, R. Lafite. (2007). The effect of wave‐induced turbulence on intertidal mudflats:

Impacts of boat traffic and wind. Continental Shelf Research Volume 27 Issue 5. Elsevier Ltd. 594‐61 Eduardo Siegle; Lauro J. Calliari. (2008). High energy events and short‐term changes in superficial beaches sediments.

Brazilian Journal of Oceanography. Volume 56 No 2. Scientific Electronic Library. 149‐152. Sorensen, Robert M., (1930). Basic wave mechanics for coastal and ocean engineers. Lehigh University, United State

of America.


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HOMOTOPY PERTURBATION METHOD AND HOMOTOPY ANALYSIS METHOD IN SOLVING ORDINARY DIFFERENTIAL EQUATIONS

NOOR AMALINA NISA ARIFFIN, SHAIFUL BAKRI ISMAIL Department of Applied Science and Advance Technology


Abstract

Differential equations are equations which relate an unknown function of one or several variables to the values of the function itself and its derivatives. Differential equation arises in many areas of science and technology, specifically when‐ever relationships involving some continuously varying quantities which are modeled by functions. Differential equations play a prominent role in engineering, physics, economics and other disciplines. The purpose of this paper is to compare two mathematical methods used for finding solutions for ordinary differential equation and system of ordinary differential equation. Homotopy Analysis Method and Homotopy Perturbation Method will be used to find the approximate analytical solutions. An ordinary differential equation and system of ordinary differential equation will be solved using these two methods. Our aim is to compare which method between Homotopy Analysis Method and Homotopy Perturbation Method is the best method to solve ordinary differential equation and system of ordinary differential equation. Actual solution to both equations will be used as a guideline to make a decision between these two methods. Keywords: Homotopy, perturbation, differential equation Introduction Mathematical modeling of physical phenomena in science and engineering often lead to differential equations. Mathematical model is a representation of the essential or core aspects of an existing system (or a system to be con‐structed) which presents knowledge of that system in usable form (Eykhoff,1974). Mazur (2006) defines mathematical modeling as a process of creating a mathematical representation of some phenomenon in order to gain a better under‐standing of that phenomenon. By using mathematical modeling we can easily analyze and solve this system by using sev‐eral techniques. Differential equations are used to analyze certain phenomena that occur in our daily life such as falling bodies, spread of contagious disease, population growth, fluid mixtures and many others. Homotopy Perturbation Method and Homo‐topy Analysis Method are examples of approximate analytical methods. Approximate analytical methods yields approxi‐mate answers in the form of a formula. Numerical methods on the other hand, yield approximate answers in the form of a number.


Received: 31st October 2011, Revised: 5th December 2011, Accepted: 30th December 2011


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There are many methods from the past up to now to give numerically approximate solutions of differential equation such as Euler Method, Runge‐Kutta Method, Multistep Method, Taylor Series Method, Hybrid Method, Meshless Method and others. There are also many methods which give analytically approximate solutions like the artificial small parameter method, the d‐expansion method, adomian decomposition method including the two methods that will be used in this paper which are Homotopy Analysis Method and Homotopy Perturbation Method. Numerical method and approximate analytical method can be used to find the solution for ordinary differential equa‐tion either first order differential equation or higher‐ order ordinary differential equation. For the higher‐order ordinary differential equation using numerical methods, the differential equation will usually be reduced to a system of first order differential equations before the numerical method is applied to solve the problem as explained by Bahrom (1992). In this paper, first‐order ordinary differential equation and system of first‐ order ordinary differential equation will be solved using two different approximate analytical methods which are Homotopy Analysis Method and Homotopy Pertur‐bation Method. The population growth model has been chosen to represent first order differential equation. This popula‐tion growth equation was proposed by Belgian mathematician‐biologist, Verhulst in 1840.

Objectives

The objectives of this research are:

1. To solve both population‐growth model which represents first order ordinary differential equation and to solve a system of ordinary differential equation using Homotopy Analysis Method and Homotopy Perturbation Method.

2. To estimate error value by comparing the result obtained using Homotopy Analysis Method and Homotopy Per‐turbation Method with the actual solution of each case.

3. To determine and decide what method is the best method to solve ordinary differential equation.

Methodology

The basic concepts of Homotopy Analysis Method and Homotopy Perturbation Method will be studied and applied to solve both population‐growth Model that represents the first order of ordinary differential equation and a system of ordi‐nary differential equation. From the result obtained, all solutions will be compared to the actual solutions and value of error for each case will be calculated. Then all results collected will be presented in graph and table forms. Comparison between the solutions obtained by Homotopy Analysis Method and Homotopy Perturbation Method will be analyzed. At the end, a decision on which method is the best method to solve ordinary differential equations will be made based on which method has given a solution that is close and converge to the actual solution and give the smallest error value.

ORDINARY DIFFERENTIAL EQUATION Differential equation plays a vital role in the solution of many problems encountered when modeling physical phe‐nomena. Differential equations are equations that involve derivatives of some unknown functions. An ordinary differential equation (ODE) is a differential equation in which the dependent variable (the unknown function) are functions of one independent variable the quantity upon which the dependent variable depends. An ODE of order n is an equation or can be put in the following form:

y(n) = F(x, y, y’,….., y(n‐1) )


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wherey, y’,….., y(n) are all evaluated at x.The independent variables x belongs to some intervalI, (I may be finite or infinite), the function F is given and the function y =y(x) is unknown (Arora,2009). The order of a differential equation is the order of highest derivative of the unknown function that appears in the equation.While working with higher order ODE’s it can be reduced to first order equations system by means of simple transformations. Example: if the differential equation in the form of: (Finizio and Ladas, 1981)

Y(n) = F(x, y(n‐1) ) (1.1)

containing only two consecutive derivatives y(n) and y(n‐1) can be reduced to first order by means of the transformations

w= y(n‐1) (1.2) In fact differentiating both sides of equation (2) with respect to x we find:

w’=y(n) Hence from (1) :

w’=F(x,w)

While second order differential equation of the form:

Y’’= F(y, y’) (1.3)

(they should not contain x) can be reduced to first order by means of the transformation

w=y’ (1.4) In fact, from (4) (using the chain rule):

Thus equation (3) becomes (Finizio and Ladas, 1981) :

= F(y,w)

which is first order with independent variable y and unknown function w. A solution of a differential equation is a differen‐tiable function that satisfies the equation on some interval I=(α,β). For example:

u(t)= et satisfies u’’ = u for all t because

u’(t)=et and u(t)=et


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For this reason et is called a solution of u’=0 (Merle, 1998). According to Finizio and Ladas (1981), every linear ODE possesses a family of solutions. A specific number of this fam‐ily is determined by supplementing the ODE by conditions on the solutions. Suppose that b1, b2, ….,bn are n fixed real num‐bers. Then the initial value problem (for the nth order linear ODE) is given by:

U(n) + p1(t)u(n‐1) + …. + P n‐1(t)U

(1) + Pn (t)u = f(t)

U(t0) = b1 u’(t0)= b2 ,…., u(n‐1)(t0) = bn

Note that: (Finizio and Ladas, 1981)

1. t0 is the value of the independent variable at which all initial conditions are imposed. 2. There are as many initial conditions as the order of differential equation.

Homotopy Analysis Method A variety of methods therefore were proposed to find approximate solutions. One of the most recent popular tech‐nique is the homotopy analysis method, which is a combination of the classical perturbation technique and homotopy concept as used in topology. Homotopy Analysis Method has been developed by Liao in 1992 to obtain series solution of various differential equa‐tion problems. This technique as successful been used to several differential equation problem such as viscous flows of non‐Newtonian fluids, non‐linear water waves, heat transfer and so on. This method has many advantages over the classical methods which is independent of a small or large quantities. Thus, it can be applied no matter if equations and boundary initial condition contain either small or large quantities . Also, it does not require a discretization or linearization, non‐linearity assumptions (Turkyilmazoglu, 2010). The Homotopy Analysis Method consists of the auxiliary parameter h which is used to ensure the convergence region of solution series. Many powerful methods proposed to solve linear and non‐linear differential equations, among them, the Homotopy Analysis Method enjoys many advantages such as freedom in choosing initial approximations and auxiliary linear operators and gives an efficient approximate analytical solution with high accuracy, minimal calculation and avoid‐ance of physically unrealistic assumptions (Liao, 1992). Homotopy Analysis Method is one of the powerful techniques to solve linear and non‐linear differential equations which was studied by a large number of researchers whose work has been devoted to the application of the HAM to a wide class in sciences and engineering such as Domairry (2010) who applied HAM in heat transfer.


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Advantages of Homotopy Analysis Method From previous discussion Homotopy Analysis Method has many advantages compared to the other perturbation and non‐perturbation methods. Liao (1992) proposes the advantages of the Homotopy Analysis Method as follows:

Mainly it is independent of a small or large quantities.

So HAM can be applied no matter if governing equation and boundary or initial conditions contain either small or large quantities.

The HAM also avoids discretization and provides an efficient numerical solution with high accuracy, minimal cal‐culation, avoidance of physically unrealistic assumptions.

Furthermore, the HAM always provides us with family of solutions expressions in the auxiliary parameter , the convergence region and rate of each solution might be determined conveniently by the auxiliary parameter h.

Basic concepts of Homotopy Analysis Method Liao (1992) described the early form of the Homotopy Analysis Method. The essential idea of this method is to intro‐duce a homotopy parameter, say p, which varies from 0 to 1 and a nonzero auxiliary parameter so‐called the convergence control parameter h. At p = 0, the system of equations usually has been reduced to a simplified form which normally ad‐mits a rather simple solution. As p gradually increases continuously toward 1, the system goes through a sequence of de‐formations, and the solution at each stage is close to that at the previous stage of the deformation. Eventually at p = 1, the system takes the original form of the equation and the final stage of the deformation gives the desired solution. To illustrate the basic ideas of this method, consider the nonlinear boundary value problem (Turkyilmazoglu, 2010):

N(u(r)) = 0; r є Ω, ; r є Ґ (2.1)

Where u(r) defined over the region Ω is the function to be solved under the boundary constraints in B defined over the boundary Ґ of Ω. The homotopy analysis technique defines a homotopyu(r, p) : R × [0, 1] àR so that

H(u, p) = (1 − p)[L(u) − L(u0)] + phN(u) (2.2) Where L is a suitable auxiliary linear operator, u0 is an initial approximation of equation (2.1) satisfying exactly the bound‐ary conditions. It is obvious from equation (2.2) that

H(u, 0) = L(u) − L(u0), H(u, 1) = N(u) (2.3)


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As p moves from 0 to 1, u(r, p) moves from u0 (r) to u(r). In topology, this is called a deformation and L(u) − L(u0) and N(u) are said to be homotopic. Our basic assumption is that the solution of equation (2.2) when equated to zero can be ex‐pressed as a power series in p(Turkyilmazoglu, 2010 ; Liao, 1992):

u(r, p) = u0 (r) + pu1(r) + p2u2(r) + ∙ ∙ ∙ = (2.4)

The appropriate solutions of the coefficients uk(r) in (2.4) can be found from the homotopy deformation equations. Hence, the approximate solution of equation (2.1) can be readily obtained as: (Turkyilmazoglu, 2010 ;Liao, 1992):

u(r) = = (2.5)

It was found that the auxiliary parameter h can adjust and control the convergence region and rate of homotopy se‐ries solutions (2.4). Whenever the series (2.4) is known to be convergent, then (2.5) represents the exact solution of (2.1). Homotopy Analysis Method is the method that can give the solution which converges to the exact solution. Parameter h in this Homotopy Analysis Method play an important role in control the range of convergence of the solutions.

Homotopy Pertubation Method Homotopy Perturbation Method was proposed by He (1998). The Homotopy Perturbation Method that has been ap‐plied for differential equation problem continuously deforms the difficult problem under study to an easy problem to solve. Recently the Homotopy Perturbation Method has been used to solve integral equation. A few mathematicians have applied Homotopy Perturbation Method into their research. They are J. Biazar, Ghazvini and M. In contrast to the tradi‐tional perturbation methods, this technique does not require a small parameter in an equation. In this method , according to the homotopy technique, a homotopy with an embedding parameter p ε [0,1] is constructed, and the embedding pa‐rameter is considered as a “small parameter” which can take the full advantages of the traditional perturbation method and homotopy techniques. Basic Concepts of Homotopy Perturbation Method To illustrate the basic concepts of Homotopy Perturbation Method, consider the following non‐linear functional equation (Behzad, 2010):

A(u) = f(r) , r є Ω (2.6)

with the following boundary conditions:

B(u, ) = 0r є Ґ (2.7)


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Here A is a functional operator, B is a boundary operator, f(r) is a known analytic function and Ґ is the boundary of the domain Ω. Generally speaking, the operator A can be decomposed into two parts L and N, were L is a linear and N is a non‐linear operator. Therefore (4. 6) can be rewritten as the following (Behzad, 2010):

L(u) + N(u) –f(r) = 0 (2.8)

We construct a homotopy1/(r,p) : Ω x [0,1] àR which satisfies:

H(v,p) = (1‐p)[L(v)‐ L(U0)] + p[A(v) –f(r) ] = 0 p є [0,1] , r є Ω (2.9)

Or H(v,p) = L(v) – L(u0) + pL(U0) + p[A(v) – f(r) ] = 0 p є [0,1] , r є Ω (2.10) Where U0 is a initial approximation to the solution of equation (4. 6). In this method the homotopy Perturbation pa‐rameter, p is used to expand the solution as a power series says:

V = V0 + pV1 +p2V2 + …… (2.11)

Usually an approximation to the solution will be obtained by taking the limit, as p tends to 1, (Behzad, 2010) i.e.:

U= (2.12)

Like other non‐perturbation techniques such as Lyapunov’s artificial small parameter method and Adomian’s de‐composition method, The Homotopy Perturbation Method can give approximations even if a problem does not contain small or large parameters. However our research indicates that this is not the key point for solving differential equation problems. Using the Homotopy Perturbation Method, one might get divergent results even for a linear problem. Discussion Ordinary Differential Equation

Firstly a simple ordinary differential equation will be considered:

With initial value Y(0)=1 and from the equation (5.1), the actual solution was given as:


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Actual solution From the above equations which represent the actual solution of ordinary differential equation chosen, the graph for the actual value was plotted by using MATLAB program. The graph for the actual solutions of ODE as in the Figure 1.

Figure 1: The actual solution of the ordinary differential equation as in equation

Solution by using Homotopy Perturbation Method In this section, ordinary differential equation has been solved by Homotopy Perturbation Method. 3‐term and 5‐term

expansion of Homotopy Perturbation Method was applied to get the approximate analytical solution for this ordinary

differential equation. From observation, it shows that 5‐term give approximate answer that close to the actual solution.

So as a conclusion 5‐term expansion of Homotopy Perturbation Method is the better expansion for obtain a solution

of ordinary differential equation but as t increase the solution by Homotopy Perturbation Method is diverging from the

actual answer. From the experiment that has been done it can be clearly seen weakness of Homotopy Perturbation

Method is it only valid for certain value of parameters. When , Homotopy Perturbation Method will diverge from the

actual solution.

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 21

2

3

4

5

6

7

8


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Table 1: Comparison Result obtained by 3‐term and 5‐term Homotopy

Perturbation Method for ordinary differential equation

Solution by using Homotopy Analysis Method Now this ordinary differential equation will be solved by Homotopy Analysis Method. This method has been gener‐ated using Mathematic 7.0. 3‐term, 7‐term and 10‐term Homotopy Analysis Method were generated to see how many terms will Homotopy Analysis Method needs to converge to the exact value.

Table 2: Comparison Result obtained by 3‐term, 5‐term and 10‐term Homotopy Analysis Method for ordinary differential equation


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After this ordinary differential equation has been solved by using 3‐term,5‐term and 10‐term Homotopy Analysis Method it clearly show that 10‐term expansion of the Homotopy Analysis Method give the best answer which close to the actual solution. The Homotopy Analysis Method solutions contain an auxiliary parameter, h which provides a convenient way of controlling the convergence region of the series solutions. Comparison and observation By comparison that have been made, it can be conclude that 5‐term Homotopy Perturbation Method and 10‐term Homotopy Analysis Method will give solution that close to the exact solution. To compare between this two methods, comparison between 5‐term Homotopy Perturbation Method and 5‐term Homotopy Analysis Method have been made with the exact solution. Table for this comparison is shown in Table 3.

Table 3: Comparison Result obtained by Homotopy Perturbation Method and Homotopy

Analysis Method for ordinary differential equation with exact solution

It clearly show that solutions obtained for ordinary differential equation solved by Homotopy Analysis Method con‐verge to the exact solutions. Solutions obtained by this method have smallest error value compared to the solutions ob‐tained by Homotopy Perturbation Method. Even though the solutions from Homotopy Perturbation Method seem to con‐verge to the actual solution, this is valid only for a small portion of the valid values of the parameters. Furthermore even in the case where the Homotopy Perturbation Method is valid, the approximate solution given by the Homotopy Perturba‐tion Method is not always accurate. System of Ordinary Differential Equation

The system of ODE considered as below:


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With the initial condition X(0) = 1 and Y(0) = 1, the actual solution for this system is:

Actual solution From the above equation which represents the actual solution for system of ordinary differential equation chosen, the graph for the actual value was plotted by using MATLAB program. The graph for the actual solution of system of ODE is as in the Figure below:

Figure 2: Actual solution for system of ODE

Solution by using Homotopy Perturbation Method In this section, ordinary differential equation was solved by Homotopy Perturbation Method. 3‐term and 5‐term ex‐pansion of Homotopy Perturbation Method have been applied to get the approximate analytical solution for this ordinary differential equation. It shows that 5‐term has given an approximate answer that is close to the actual solution. So, it can be conclude that 5‐term expansion of Homotopy Perturbation Method is the better expansion for obtain‐ing a solution of ordinary differential equation but as t increased the solution by Homotopy Perturbation Method is di‐verges from the actual answer.

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8


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Table 4: Comparison Result obtained by 3‐term and 5‐term Homotopy Perturbation

Method for system of ordinary differential equation

Solution By using Homotopy Analysis Method Now system of ordinary differential equation will be solved byHomotopy Analysis Method. This method has been gen‐erated using Mathematica 7.0. 3‐term, 5‐term and 10‐term Homotopy Analysis Method have been generated to see how many terms does Homotopy Analysis Method need to converge to the exact value. The program for calculation 3‐term expansion of this method was viewed in Appendix D. The expansion of the solution obtained from the program as below:

The appropriate h–curve for this solution as below:

Figure 3: h‐curve of 3‐term Homotopy Analysis Method for system of differential equation


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The result obtained for 3‐term, 5‐term, and 10‐term of Homotopy Analysis Method with h = ‐0.8 below:

Table 5: Comparison Result obtained by 3‐term, 5‐term and 10‐term Homotopy Analysis Method for system of ordinary differential equation

Ordinary differential equation that been solved by using 3‐term,5‐term and 10‐term Homotopy Analysis Method shows that 10‐term expansion of the Homotopy Analysis Method give the best answer which close to the actual solution. The Homotopy Analysis Method solutions contain an auxiliary parameter, h which provides a convenient way of control‐ling the convergence region of the series solutions.

Comparison and observation By the comparison that has been made, it can be conclude that 5‐term Homotopy Perturbation Method and 10‐term Homotopy Analysis Method will give a solution that is close to the exact solution. In comparing between these two meth‐ods, we have made a comparison between 5‐term Homotopy Perturbation Method and 5‐term Homotopy Analysis Method with the exact solution. A table for this comparison shown below:

Table 6: Comparison Result obtained by Homotopy Perturbation Method and Homotopy

Analysis Method for system of ordinary differential equation with exact solution


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It can be clearly seen that solutions obtained for Ordinary Differential Equation solved by Homotopy Analysis Method converged to the exact solutions. Solutions obtained by this method have smallest error value compared to the solutions obtained by Homotopy Perturbation Method. Even though the solutions from Homotopy Perturbation Method seem to converge to the actual solution, but this is valid only for a small portion of the valid values of the parameters. Furthermore even in the case where the Homotopy Perturbation Method is valid, the approximate solution given by the Homotopy Perturbation Method is not always accurate. Discussion From the results obtained, which have been presented in graph and table forms, it is clear that Homotopy Analysis Method can give a solution which converge to the actual solution for all cases as compared to the Homotopy Perturbation Method. In the first and the second cases for simple ordinary differential equation and system of ordinary differential equa‐tion, different values of term expansion for Homotopy Perturbation Method and Homotopy Analysis Method have been applied to see the effect or value of term expansion. Throughout the experiment that was conducted earlier, it clearly show that Homotopy Perturbation Method with 5‐term expansion and Homotopy Analysis Method with 10‐term expan‐sion have given the answers that are close to the exact solutions. So to make a comparison with the actual solution, the 5‐term Homotopy Perturbation Method and 5‐term Homotopy Analysis Method will be taken. Comparison that have been done above show that Homotopy Perturbation Method gives the solution that is close to

the exact solution but it only valid for certain number of valid parameter. The solution obtained by the Homotopy Pertur‐

bation Method diverges as t . The solutions obtained by applying Homotopy Analysis Method are more converged to

the exact solution. Throughout these cases, it have been demonstrated that the solution of Homotopy Analysis Method

can be controlled by an auxiliary parameter h which play an important role to control the range of convergence. By using

the optimal value of parameter h, solutions by Homotopy Analysis Method could converge to the exact solution.

Conclusion Many mathematical modeling of physical phenomena in science and engineering often lead to the differential equa‐tions. There are many of methods, from the past up to now, to give numerically approximate solutions differential equa‐tion such as Euler methods, Taylor series methods, hybrid methods, meshless method and others. There are also many methods which give analytically approximate solutions like perturbation methods, Adomian Decomposition Method, Homotopy Analysis Method and many more. In Section 2, it clearly show that differential equation plays an important role in the solutions of many problems. First order of ordinary differential equation and its solution has been discussed throughout this chapter. In this chapter it shows that how high order ordinary differential equation can be reduced to the first order ordinary differential equation. The results obtained from all cases showed that both methods have given solutions that converged to the exact solu‐

tion but for Homotopy Perturbation Method, it is only valid for certain numbers of parameters (i.e. and it will be easier when both methods were applied by using Mathematica 7.0 program. It shows that Homotopy Analysis Method has given solutions that mostly converged to the actual solution compared to the Homotopy Perturbation Method. Since Homotopy Analysis Method has the parameter h which controls the range of convergence, therefore it can be conclude that this method is therefore the best method in finding solutions for the differential equation as compared to the other methods.


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The Homotopy Analysis Method can guarantee the convergence of the series solutions by auxiliary parameters espe‐cially so‐called convergence‐controller parameter h. It is shown in this dissertation that h also plays basic role in prediction of multiplicity of solutions of differential equation problems. Different from perturbation method, the validity of the Homotopy Analysis Method is independent on whether or not there exist small parameters in considered ordinary differential equation problems. Therefore it provides us with a power‐ful analytic tool for ordinary differential equation problems. Therefore it can be conclude that Homotopy Analysis Method is the best method to solve ordinary differential equation since Homotopy Perturbation Method will only valid for a small portion of parameters. Furthermore, even in the case the Homotopy Perturbation Method is valid, the approximate solu‐tions give by the Homotopy Perturbation Method is not always accurate. References Bahrom, S. (1992).PersamaanPembezaan, p. 79‐101.Malaysia : Unit Penerbitan Akademik Universiti Teknologi Malay‐sia Lioa, S. (2004). Beyond Perturbation : Introduction to the homotopy analysis method , p. 79‐84.Amerika Syarikat : Chapman & Hall/CRC. Wang, Z., Zou, L.,Zhang, H. (2007). Applying homotopy analysis method for solving differential‐difference equation [Online]. [Accessed 2th November 2010]. Available from World Wide Web: http://linkinghub.elsevier.com/ Bataineh, S.A., Noorani, M.S.M &Hashim, I. (2007).Solving systems of ODEs by homotopy analysis method [Online].[Accessed 26thDisember 2010]. Available from World Wide Web: http://linkinghub.elsevier.com/retrieve/pii/S1007570407001463

Odibat,Z and Bertelle, C. (2006). Application of Homotopy Perturbation Method for Ecosystem Modeling [online].[Accessed 20th December 2010]. Available from World Wide Web: http://www.springerlink.com/ Weisstein, EW. (2003). Ordinary Differential Equation [online].[Accessed 14th January 2011]. Available from World Wide Web: http://mathworld.wolfram.com/OrdinaryDifferetialEquation.html Arora,I. (2009). Application of Differential Equation in Engineering: Numerical Analysis [online]. [Accessed 14th February 2011]. Available in World Wide Web: http://www.scribd.com/ Jack Goldberg, Merle C.Potter. (1998). Differential Equations, A system Approach, 1stedn. United States of America. Simon & Schuster /A Viacom Company. Finizio, Ladas. (1981). Ordinary Differential Equation with modern applications, 2ndedn. United States of America: Wadsworth, Inc.

MarkMcGinley.(1992). Population Growth Rate [Online].[Accessed 17th February 2011]. Available in World Wide Web: http://www.eoearth.org/article/Population_growth_rate Population Growth (2010) [Online].[Accessed 4th January 2011]. Available in World Wide Web: http://www.otherwise.com/population/index.html

http://linkinghub.elsevier.com/

http://linkinghub.elsevier.com/retrieve/pii/S1007570407001463




http://www.springerlink.com/

http://mathworld.wolfram.com/OrdinaryDifferetialEquation.html

http://www.scribd.com/

http://www.eoearth.org/article/Population_growth_rate

http://www.otherwise.com/population/index.html


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Population Growth Model (2010) [Online]. [Accessed 28th January 2011]. Available in World Wide Web: https://www.msu.edu/user/vieirast/popmdl.htm Fall. (1999). Population Growth Model [Online].[Accessed 13th January 2011]. Available in World Wide Web: https://www.msu.edu/user/vieirast/popmdl.htm Turkyilmazoglu,M. (2010). Convergence of the homotopy Analysis Method. 1‐12 Domairry, G., Mohsenzadeh, A., Famouri, M. (2007). The application of homotopy analysis method to solve nonlinear dif‐ferential equation governing Jeffery‐Hamel flow, 85‐95.

https://www.msu.edu/user/vieirast/popmdl.htm

https://www.msu.edu/user/vieirast/popmdl.htm


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PETROLEUM TECHNOLOGY: A BRIEF TECHNICAL REVIEW

ISHAK HAMZAH1, ABDUL AZIZ BIN ABDUL RAHIM2, AZIZ ABDULLAH3 1Department of Marine Design Technology

2 Department of Applied Science and Advanced Technology, 3Department of Marine Construction and Maintenance Technology


Abstract A technical review on petroleum technology helps provide an insight to the lay man on the basic components of pe‐troleum that consists of crude oil and natural gas. The outcome to this review at least helps to generate interest and awareness to the community in appreciating the existence of this black oil which has become an important component to our daily life. In capturing the readers’ attention, the article begins with the origin of petroleum, its distribution route through pipeline or tanker for export and ends with the testing analysis of liquid fuels. Keywords: Petroleum, Hydrocarbons, Refining process, Distillation process Introduction Our daily life has become very dependent on the petroleum products. Directly or indirectly we use petrol or diesel for our vehicles and we utilize gas for cooking activity. Other derivatives of petroleum product, namely kerosene, fuel oils and asphalt are generated from the refinery through the fractional distillation process for industrial purposes. More than 3000 products are derived from petroleum base or natural gas. Plastics, detergent, paints, fertilizers, and cosmetics are among the common ones. Even proteins and vitamins are produced from oils. Although many of us may not be familiar with the petroleum industry, this article will briefly help explain the fundamental aspects of petroleum and its associated technology. Objective The purpose of this article is to provide a comprehensive technical review on the oil and gas technology and their re‐lated industries. It will also discuss basic refining and processing of oil and gas to enable readers to appreciate better the importance of petroleum and its derivatives.


Received: 27th November 2011, Revised: 7th December 2011, Accepted: 23rd December 2011


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Theory of Petroleum The word ‘petroleum’ comes from an old Greek word for rock that is ‘petra’ and the Latin word ‘oleum’ for oil. Since oil is usually found in rocks, hence it is called ‘rock oil’ or petroleum. The main components of petroleum are crude oil and natural gas which are chemically referred as hydrocarbon (hydrogen and carbon). The liquid hydrocarbon is crude oil, while its gaseous state is called natural gas. Most scientists believed that oil and gas were developed from the remains of organic matters (millions of years ago) such as microscopic plants and animals which thrived in seas and rivers, and they subsequently settled and lay buried in sand and mud. Eventually these remains become hardened into rocks and later were transformed to petroleum due to heat, pressure and chemical processes. Petroleum is normally found in sedimentary rocks such as limestone, sandstones, conglomerates and shale either on land or in the sea. Oil and gas are trapped in the sedimentary rocks like pools of water known as ‘reservoir’. This kind of sedimentary rocks are said to be permeable when the pores of the rocks are connected and allowing oil and gas to move or flow freely between the pores as shown in Figure 1 and Figure 2.

Figure 1: Porous rocks with many tiny openings or pores

Figure 2: Permeable rocks with connected pores

Usually oil, gas and water are separated in a reservoir. Water at the bottom, oil in the middle and gas being the light‐est, would be on the top. These three components are often blocked or trapped by a layer of impermeable rocks known as ‘cap‐rock’ as shown in Figure 3. Crude oil contains a chemical element known as Sulphur. Low sulphur content results in ‘Sweet crude’ while higher sulphur content results in ‘Sour crude’ oil. The crude oil colour ranges from either green to yel‐low or brown to black. Some are sticky or heavy, while some are thinner and heavier. Natural gas components are namely methane, ethane, propane, butane, pentane and other heavier hydrocarbons. Natural gas found with oil is called ’associated gas’ while found on its own is known as ‘non‐associated gas’. Natural gas is found below the earth surface and subjected to high pressure and temperature. If it is brought up above the earth sur‐face, its heavier components become liquid called the condensate.


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Figure 3: Oil and gas reservoir between impermeable rocks

Common Drilling Activity There are several types of drilling rigs to suit each climatic conditions and water depths. These drilling rigs are self‐contained and self supporting. Once significant reserves of oil and gas are found beneath the seabed, permanent plat‐forms are to be installed to ease drilling operations. Platforms are fixed structures resting on tall legs driven into the sea‐bed to a depth of about 30 meters below the sea water surface. These platforms height must be above the sea waves, even during worst weather conditions.

Fractional Distillation of Crude Oil Crude oil is classified into three different categories of hydrocarbons namely: Paraffinic, Naphthenic and Asphaltic. In fractional distillation process, crude oil is heated to about 3500 C in a furnace before it is piped to a fractionating tower as shown in Figure 4. The fractionating tower contains numerous trays at about 60 centimeters interval to facilitate the sepa‐ration process of products. Oil vapours rise up the tower and condensed to liquid at the different level of trays. Unvapour‐ised oils will be drained down the tower. Products with high boiling points will be collected at the base of the tower as ‘residue’. Those products with the intermediate boiling point will accumulate in the middle trays, while products with the lower boiling point will be condensed at the top of the tower. Light products such as LPG gas, gasoline and naphtha are taken off at the top of the tower. The heaviest products such as asphalt and tar are drawn off at the bottom of the tower. Products of the fractionating tower may then be used directly or recombined to form other products.

Figure 4: Fractional Distillation Process [Source: Institute of Petroleum, UK]


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Categories of Hydrocarbon

The four main categories of hydrocarbon are as follows;

Paraffinic : example Methane Gas (CH4), used for vehicle

Naphthenic : example Cyclo‐Butane (C5H10), used for industrial application

Aromatic : example Benzene (C6H6), used for petrol blending

Olefin : example Ethylene (C2H4), used for petrochemical products

Crude Refining Process Crude is heated in fractional tower and the distillates are tapped off based on boiling points as described earlier. The vacuum distillation process is to distill for heavier fraction at lower temperature to avoid oil cracking, such as in the case of lubricating oil. However, to further improve the quality of distillates especially for specialized products, such as aviation and automo‐bile fuels, they have to undergo complex processes, namely called catalytic and thermal cracking, alkylation and cyclisa‐tion. Some of the improvements may results in higher ignition quality, lower knock rating and greater sulphur removal. Basic refinery process layout is as shown in Figure 5 below for further understanding on the refining technology.

Figure 5: Basic Refinery Layout (Jackson and Morton, 2006)


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Processing of Natural Gas Natural gas production involves three types of processing comprise of slug removal, cooling and separation based on the products’ boiling point. A typical gas processing plant and its product distribution route is as shown at Figure 6. Process 1: Removal of Slug Natural gas containing liquid slug needs to be processed into petroleum in a refinery. This slug is normally trapped in slug‐catcher. Process 2: Cooling and Separation. The trapped slug in the slug‐catcher is piped to a gas processing plant for cooling and separation of the desired gases. Propane and butane in liquid form are drawn off when cooling takes place at ‐120 C. To produce ethane, the gas needs to be further cooled at ‐800 C. After propane, butane and ethane are removed, the remaining gas is methane only. Further treatment is required before the methane gas is ready for use in homes and industries and normally the gas is transported through pipelines. Process 3: Purification During the purification process, acid gases i.e. sulphur compound, carbon dioxide and water are removed.

Figure 6: Gas Processing Plant and Its Distribution Route [PETRONAS Bulletin 1985]


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Testing of Liquid Fuels and Implication Density Storage of fuels is often based on density which is defined as mass to volume relationship. It is measured using a den‐sity meter giving units in kgm‐3. Improper selection of fuel density will have adverse effects on bunker capacity, choice of heating arrangement, foul injectors and overflow of purifiers. Viscosity It is defined as resistance to fluid flow due to friction drag effects. Kinematic viscosity is normally used and measured in centistokes (Cst) at 50⁰C. Temperature and viscosity are closely related in the choice of oils. For atomization of fuels, it is necessary to heat high viscosity of oils to maintain about 30 Cst at the injector and preferably 13 Cst for internal com‐bustion engine. The viscosity of diesel fuels is about 7 Cst at 38⁰C. Flash Point The minimum temperature at which an oil or fuel gives off flammable vapour is known as the flash point. Flash point is indicative of fire and explosion hazard for storage and transport of oils. Oils with flash point below 22⁰C, such as gasoline and Benzene are classified dangerous and highly flammable. Kerosene and vapourising oils have flash points between 22⁰C and 66⁰C. Marine oils, diesel and fuel oils are safe due to their flash points of above 66⁰C. Marine oils should have minimum flash point of 66⁰C and be heated above 52⁰C. High viscosity oils need to be heated to produce atomization and to ensure control of heat to heater on the suction side of the fuel pump to avoid oil vapourisation and occurrence of explosion vapour. Calorific Value It is defined as the heating value for the complete combustion of mass of fuels. Approximate heat energy of fuels are 34 MJ/kg for coal, 42 MJ/kg for fuel oil, 45 MJ/kg for diesel oil and 50 MJ/kg for pure hydrocarbon (85% Hydrocarbon + 15% Hydrogen) (Jackson and Morton, 2006). Fuels will always loss its calorific value to some extent during storage. Carbon Residue The test utilized the Conradson Carbon Test Method (Jackson and Morton, 2006) to determine the residual carbon content after burning of the oil when using high viscosity fuels in the internal combustion engine. Fire Point It is defined as the temperature at which volatile vapours given off from heated oil is ignited. The ignition temperature is normally about 40⁰C higher than the flash point temperature of fuel oils. Research Octane Number (RON) An indication of knock rating of the internal combustion engine (spark ignition) and may result in pre‐ignition overheat and damage to the engine if fuel of improper RON number is used. This is due to engine condition and type of fuels used that cause a rise in the temperature and pressure above the spontaneous ignition point. The effects would be detonation (engine knocking) and occurrence of heavy shock wave. The test is conducted by using a standard engine fitted with an electronic detonation detector.


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Cetane Number/Cetane Index (CN/CI) Cetane Number (CN) is an indication of ignition quality of the compression ignition engine or diesel engine especially during cold starting condition. It is important to understand that the time interval between fuel injection and firing (ignition delay) should not be too long to avoid excessive fuels injected which may generate high pressure condition in combustion chamber during ignition, henceforth resulting in detonation or engine knocking. The test is normally carried out using a standard engine running under fixed condition with a variable compression ratio to give a standard ignition delay to indicate a Cetane Number. Density of fuel is also Cetane Number indicator such as for 850 kg/m3 density the CN is about 61 and for 950 kg/m3 density the CN is about 37. High speed engine above 13.3 revolutions/second would require a CN of 48 minimum, while for low speed engine be‐low 1.7 revolutions/second a CN of 15 will be the minimum requirement. Diesel fuel is thus not compatible to use in the petrol engine due to detonation caused by low Octane Number. Typical Analysis of Fuel Oils Typical analysis of petrol, kerosene, diesel and residual has been tabulated as in Table 1 for better understanding on the relationship between properties required. It is noted that the heavier the oil the higher the viscosity and flash point would be but the calorific value is low. This shows that the fuels need additional heating and purification. The effects will reduce the storage bunkering vol‐ume but the fuel consumption of engine will increase.

Table 1: Typical Analysis of Fuel Oils (Jackson and Morton, 2006)


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Interpretation The production of petroleum had promoted economic development in many countries today. Without this black oil the industry may not have developed into what we are seeing nowadays. The petroleum technology has developed rapidly to meet the requirements for mankind with over 3000 products in the market. The products keep increasing as the tech‐nology advances. As consumers we should be aware of the technical issues that arise and increase our knowledge on pe‐troleum technology to our benefits. The processes involved from exploration until the end product have been described precisely in this article that should help us become more aware and grateful on the economic benefits of petroleum to mankind.

Conclusion Petroleum has obviously become an important part of our daily life. We depend a lot on this black oil to ensure the fulfillment of our needs. Unfortunately, we seldom value its existence because of our poor knowledge of its origin, explo‐ration and processing. Thus, it is vital to provide such an article to create interest and awareness on the importance of this product. Malaysia is blessed with 5.5 billion barrels of crude oil and 84 trillion cubic feet of natural gas reserves respec‐tively as of 2009 data (Hydrocarbon Engineering, 2010). We ought to comprehend the depletion of these reserves that may adversely affect our survival. Being grateful is not an option. References Leslie Jackson and Thomas D. Morton (2006). Reed’s General Engineering Knowledge for Marine Engineers, Adlard Coles Nautical London Hydrocarbon Engineering (2010). www.energyglobal.com Stanley G. Christensen (2004). Lamb’s Questions and Answers on the Marine Diesel Engine, Elsevier Butterworth Heinemann United Kingdom

http://www.energyglobal.com


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Abstract The solid polymer electrolytes (SPE) based on poly (ethylene oxide) complexes were prepared using solution cast tech‐nique. The electrical conductivity of the highest conducting sample was found to increase by adding different amounts of ethylene carbonate as a plasticizer at room temperature. The surface morphology of PEO complexes were then studied by using SEM. As a result, more amorphous regions are observed with increasing of salt concentration and also in PEO‐plasticized system. Keywords: Poly (ethylene oxide), Lithium ion, Ethylene Carbonate, Conductivity, Morphology Introduction

Polymer gels contain organic liquids as plasticizers. Examples of plasticizers are ethylene carbonate, EC, propylene car‐bonate, PC, low molecular weight polyethylene glycol (in liquid form), PEG, ethylene sulfite, ES. The ionic conductivity of polymer electrolytes can be optimized by adding these common types of plasticizers. According to Periasamy et al., [2000], Feuillade and Perche were the first to plasticize a polymer in 1975. Their efforts resulted in enhancing in ionic con‐ductivity close to that of liquid electrolytes. Plasticizers are mostly non‐volatile liquids of low molecular weight. Plasticizers improve flexibility of the polymer [Reddy et al., 1999]. Gel polymer electrolytes are also suitable for electrochemical de‐vices since their transport properties are quite exceptional and they have an ionic conductivity of the order of 10−3 S cm−1.

Aplasticizer can help in improving the electrical conductivity of polymer electrolytes in the following ways [Kumar and Sekhon, 2002]:

By increasing the amorphous content of polymer electrolytes at all salt concentrations; By dissociating ion aggregates present in polymer electrolytes dominant at higher salt concentrations;

By lowering the glass transition temperature, Tg.

In general, it is believed that conductivity increases as the degree of crystallinity decreases. The crystalline regions ob‐struct ion movement by blocking the paths for ion migration. The increase in amorphous region increases the free volume. The increase in free volume would facilitate the motion of ionic charge, i.e., the migration of ions through the amorphous region. The amorphous phase of the PEO‐salt polymer electrolyte has been reported to be the high conducting phase compared to the crystalline phase [Kumar et al., 2002].

EFFECT ON SURFACE MORPHOLOGY OF PLASTICIZED POLY (ETHYLENE OXIDE) BASED POLYMER ELECTROLYTES

LEEANA ISMAIL

Applied Sciences & Advanced Technology Department, Malaysian Institute of Marine Engineering Technology, Universiti Kuala Lumpur, Malaysia

___________________________________________

Corresponding author: [email protected]

Received: 7thDecember 2011, Revised: 9th January 2012, Accepted: 9th January 2012


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Morphology studies in PEO‐salt complexes can be performed using SEM. Morphology studies were performed in order to determine the effect of adding salt and plasticizer and also the use of different solvents to dissolve the polymer.

Experimental Method

Sample preparation

In this work, two types of polymer electrolytes have been prepared.

The first system is PEO + lithium acetate in which the amount of salt is varied and the amount of polymer is fixed. Total is 100 wt. %.

The second system is PEO + lithium acetate + EC in which the total weight of polymer and the salt is fixed but plasticizer, EC concentration in wt. % is varied. Again total is 100 wt. %.

1 g of the polyethylene oxide (PEO) powder was dissolved in 50 ml 1% acetic acid solution (Ajax Chemical). The mixture was stirred continuously with a magnetic stirrer for 24 hours in room temperature until the powder has fully dissolved. Different amounts of lithium acetate (LiOAc) powder which is produced by Sigma‐Aldrich were then added to the PEO so‐lutions and stirred until the salt has completely dissolved. The solutions were then poured into different glass petri dishes and left to dry at room temperature until the film have formed. Table 1 below shows the concentration of the prepared samples for this system.

To study the effect of plasticizer to PEO‐LiOAc films, the highest conducting sample of the PEO‐LiOAc film (A7) was added with ethylene carbonate (EC). This system undergoes the same process as the PEO‐LiOAc samples preparation and this time the concentration of PEO and salt (LiOAc) were fixed. Table 2 shows the amount of the prepared samples.

Table 1 The composition of polyethylene oxide doped with lithium acetate


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Electrical Impedance Spectroscopy (EIS)

Impedance spectroscopy is very useful for determining the conductivity. It is a powerful tool that can be used in char‐acterization of many of electrical properties of many materials. This refers to the real and imaginary parts of impedance over a wide range of frequencies. It helps in separating out the true bulk conductivity from conduction due to the grain boundaries and electrode‐electrolyte interfacial impedance.

The impedance spectroscopy can be measured using HOIKI 3531‐01 LCR Hi Tester that has been interfaced to a com‐puter. The frequency range is 50 Hz to 1 MHz. The film was placed in a conductivity mount, which was connected to the bridge. The impedance measurements were measured at room temperature (25˚C).

Scanning electron microscope (SEM)

The scanning electron microscope (SEM) is a type of electron microscope that images the sample surface by scanning it with a high‐energy beam of electrons in a raster scan pattern. The electrons interact with the atoms that make up the sample producing signals that contain information about the sample's surface topography, composition and other proper‐ties such as electrical conductivity.


In this work, electrical impedance spectroscopy (EIS) has been used to determine the ionic conductivity. The effect of adding salt and plasticizer on the ionic conductivity was also investigated.

Room Temperature Ionic Conductivity of the PEO‐LiOAc System

The impedance plot of pure PEO film (A1) at room temperature is shown in Figure 4. The ‐Zi and Zr plot can be ob‐served as a depressed semicircle. The bulk resistance, Rb was taken from the Zr intercept at the x‐axis. The value of ionic conductivity of pure PEO film was calculated using Equation (2) which gives the value of 2.12x10‐10 S cm‐1. This value is in reasonable agreement with that of [Sreekanth et al., 1999] and [Kumar et al., 2006].

Table 2 The composition of ethylene carbonate doped in A7


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The impedance plot of 30 wt. % LiOAc concentration (A7) is shown in Figure 5. The plot consists of a semicircle at the high frequency end and a spike at the lower frequency end of the spectrum. The value of Rb for this film (A7) is smaller compared to the value of Rb obtained for pure PEO film (A1). This implies that the value of conductivity has increased with addition of salt concentration.

The variation of room temperature conductivity with salt concentration can be observed in Figure 1. Upon addition of 5 wt. % salt (LiOAc), the conductivity starts to increase until the addition of 30 wt. % salt concentration.

The value of conductivity has increased by four orders of magnitude from 2.12 x10‐10 S cm‐1 for pure PEO sample to 2.18x10‐6 S cm‐1 for 30 wt. % LiOAc concentration. The increase in conductivity is due to the increase in the number of mo‐bile ions as the LiOAc concentration has increased. After addition of 30 wt. % LiOAc concentration, the membrane cannot be peeled easily. That is why the conductivity results is reported up to 30 wt. % LiOAc.

Table 3 lists the value of conductivity obtained for PEO‐LiOAc system at ambient temperature.

Figure 1. Variation of room temperature conductivity versus wt. % of LiOAc

Table 3. Table of conductivity values of PEO‐LiOAc system at ambient temperature


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Room Temperature Ionic Conductivity of the PEO‐LiOAc‐EC System

The PEO‐LiOAc‐EC system is called plasticized or gelled system. In this work, the ionic conductivity was also calculated using the same equation as for the previous system (PEO‐LiOAc system). The highest conducting composition of the PEO‐LiOAc system was added with ethylene carbone (EC), which was varied from 0 to 1.0 wt. %. Figure 2 shows the variation of room temperature conductivity of the PEO‐LiOAc‐EC system with different EC concentrations.

The value of conductivity for the plasticized PEO‐LiOAc system together with the standard error are listed in Table 5.

Figure 2. Plot of room temperature conductivity versus wt. % of ethylene carbonate

Table 5 Table of conductivity values of PEO‐ LiOAc‐EC system at ambient temperature


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Scanning Electron Microscopy (SEM)

Solid polymer electrolytes, SPEs have a combination of amorphous and crystalline phases due to its complexes with different metal salts. PEO is a semicrystalline polymer. The amorphous phase of the PEO‐salt polymer electrolyte has been reported to be the high conducting phase compared to the crystalline phase [Kumar et al., 2002].

Morphology studies in PEO‐salt complexes can be performed using SEM. Morphology studies were performed in order to determine the effect of adding salt and plasticizer and also the use of different solvents to dissolve the polymer.

i) Morphology of the PEO‐LiOAc System

Figure 3 shows the surface morphology for the PEO‐LiOAc system. The SEM micrographs have been obtained for all samples at room temperature.

The surface morphology of a pure PEO film formed by dissolving PEO powder in 1% acetic acid solution is presented in Figure 3(a). The surface appears as if it is made up of jointed polygon‐like structures with definite boundaries. Inside each polygon, are vein‐like structures that seem to originate from the centre of the polygon. Such morphology has been re‐ported by [Pereira et al., 2009] in polymer blends based on PEO and starch. In general, the polygon‐shape structures are smaller in size when the LiOAc salt is incorporated into the polymer. It may be deduced that LiOAc has induced changes in PEO crystallization by increasing the amorphous content of the polymer. It can be understood from the micrograph in Fig‐ure 3(e) why the sample with 30 wt. % LiOAc has the lowest crystallinity.

Figure 3. Surface morphology of PEO‐LiOAc system at room temperature;(a) pure PEO in 1% acetic acid solution; (b) 5 wt. % LiOAc; (c) 10wt. % LiOAc; (d) 20wt. % LiOAc; (e) 30 wt. % LiOAc


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ii) Morphology of the PEO‐LiOAc‐EC System

The effect on morphology of adding ethylene carbonate (EC) to the highest conducting sample of PEO‐LiOAc sys tem is shown in Figure 4. It is obvious that EC has brought changes to the surface of the highest conducting PEO‐ LiOAc sample. The micrograph in Figure 15(c) is that of the highest conducting sample. It can be observed that the surface of this sample is more continuous compared to the surface of other samples, Figure 4 (b to e) which are less continuous due to disjointed regions.

The morphology of the two types of polymer electrolytes has been analyzed by using SEM at room temperature. The

type of solvent has influenced differently the surface morphology of the pure PEO film. The effect of adding salt and plasti‐cizer has brought changes to the surface morphology of these PEO complexes. The surface of the polymer electrolyte membrane exhibits rough and smooth features indicating the different degree of crystallinity and amorphousness.

Figure 4. Surface morphology of PEO‐LiOAc‐EC system at room temperature; (a) 0.2wt. % EC;(b) 0.4 wt. % EC; (c) 0.6 wt. % EC; (d) 0.8 wt. % EC ; (e) 1.0 wt. % EC


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Conclusion

The study of morphology in PEO‐salt complexes has been determined using SEM. The effect of adding salt and plasti‐cizer has brought changes to the surface morphology of these PEO complexes In PEO‐LiOAc system, the surface appears as if it is made up of jointed polygon‐like spherulite structures with definite boundaries. On addition of EC, the spherullites structure (polygon‐like) has disappeared and no definite boundaries of polygon as in salted system.

References Kumar B., Rodrigues S.J., Koka S., “The crystalline to amorphous transition in PEO‐based composite electrolytes: role of lithium salts”, Electrochimica Acta 47 (2002) 4125‐4131

Kumar M. and Sekhon S.S., “Ionic Conductance Behaviour of Plasticized Polymer Electrolytes Containing Different Plasticizers”, Ionics 8 (2002) 223‐233

Kumar M. and Sekhon S.S., “Role of Plasticizer’s Dielectric Constant on Conductivity Modification of PEO‐NH4F Poly‐mer Electrolytes”, European Polymer Journal 38 (2002) 1297‐1304

Pereira A.G.B., Gouveia R.F., Carvalho G.M., Rubira A.F., Muniz E.C., “Polymer blends based on PEO and starch: Misci‐bility and spherulite growth rate evaluated through DSC and optical microscopy”, Materials Science and Engineering C 29 (2009) 499–504

Periasamy P., Tatsumi K., Shikano M., Fujieda T., Saito Y., Sakai T., Mizuhata M., Kajinami A., Deki S., “Studies on PVDF‐ Based Gel Polymer Electrolytes”, Journal of Power Sources 88 (2000) 269‐273

Reddy M.J., Sreekanth T., Rao U.V.S., “Study of the Plasticizer Effect on a (PEO‐NaYF4) Polymer Electrolyte and its Use in an Electrochemical Cell”, Solid State Ionics 126(1999) 55‐63

Sreekanth T., Reddy M.J., Subramanyam S., Rao U.V.S., “Ion conducting polymer electrolyte films based on (PEO+KNO3) system and its application as an electrochemical cell”, Materials Science and Engineering B64 (1999) 107–112


Volume 2 (2) 2011 115

To inculcate the research culture amongst academics, Universiti Kuala Lumpur Malaysian Institute of Marine Engineering Tech-

nology (UniKL MIMET) is publishing the Marine Frontier@UniKL Research Bulletin. For a start, the bulletin will be published four

times a year, in January, April, July and October. Original research papers, which have not been published or currently being

considered for publication elsewhere, will be considered.

Accepted Types of Research The papers accepted for the bulletins must be based on any of the following types of research:

Basic research (pure basic research and strategic basic research)

Applied research

Experimental development

Critical review

Pure basic research is experimental and theoretical work undertaken to acquire new knowledge without looking for long-terms

benefits other than advancement of knowledge.

Strategic basic research is experimental and theoretical work undertaken to acquire new knowledge directed into specified broad

areas in the expectation of useful discoveries. It provides the broad base of knowledge necessary for the solution of recognised

practical problems.

Applied research is original work undertaken primarily to acquire new knowledge with a specific application in view. It is under-

taken either to determine possible use for the findings of basic research or to determine new ways of achieving some specific

and predetermined objectives.

Experimental development is systematic work, using existing knowledge gained from research or practical experience that is

directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving

substantially those already produced or installed.

Critical review is a comprehensive preview and critical analysis of existing literature. It must also propose a unique lens, frame-

work or model that helps understand specific body of knowledge or address specific research issues.

Condition of Acceptance The editorial board considers all papers on the condition that:

They are original

The authors hold the property or copyright of the paper

They have not been published already

They are not under consideration for publication elsewhere, nor in press elsewhere

They use non-discriminatory language

The use of proper English (except for manuscripts written in Bahasa Melayu-applicable for selective only)

All papers must be typed on A4 size page using Microsoft Words. The complete paper must be approximately 3,500 words long

(excluding references and appendixes). The format is described in detail in the next section.

All papers are reviewed by the editorial board and evaluated according to:

Originality

Significance in contributing new knowledge

Technical adequacy

Appropriateness for the bulletin

Clarity of presentation

All papers will be directed to the appropriate team and/or track. The papers will be reviewed by reviewer(s) and/or editor. All

review comments and suggestions should be addressed in the final submission if the paper is accepted for publication, copyright

is transferred to the bulletin.

Please submit your paper directly to the Chief Editor- [email protected] or the Executive Editor-

[email protected] for publication in the next issue of the Marine Frontier@UniKL.

CALL FOR PAPERSCALL FOR PAPERS




Volume 2 (2) 2011 116

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