Ijsrtm vol 2 (5) august september 2014

Vol 2 (5) August 2014

International Journal of Students’

Research in Technology & Management

(IJSRTM)

Content

1. Effect of Fiber Length on the Short-Term Flexural Creep Behavior of Polypropylene

C.Subramanian, Abdulrahman Khalfan Hassan Al Mamari and S.Senthilvelan

2. E-Waste: An Emerging Problem of Innovative Society

Rahila N. Gadi and Nabeel Ahmed N.Gadi

3. Trend Analysis of Climate Variability in Salalah, Oman

Mohammed Al-Habsi , Luminda Gunawardhana

and Ghazi Al-Rawas

4. Using a New Programme to Predict Thermal Comfort as a Base to Design Energy Efficient

Buildings

Hanan Al-Khatri and Mohamed B. Gadi

5. Wadi Flow Simulation Using Tank Model in Muscat, Oman

Mohammed Al-Housni, Luminda Gunawardhana and Ghazi Al-Rawas

6. Mobile Ad Hoc Networks

Parth Panchal and Meghana Shroff

International Journal of Students’ Research in Technology & Management

Vol 2 (05), August-September 2014, ISSN 2321-2543, pg 157-162

http://www.giapjournals.org/ijsrtm.html 157

Effect of Fiber Length on the Short-Term

Flexural Creep Behavior of Polypropylene C.Subramanian

*#1, Abdulrahman Khalfan Hassan Al Mamari

#2, S.Senthilvelan

#3

#1 Shinas College of Technology, Oman

#2 Petroleum Development Oman, Oman

#3 Indian Institute of Technology Guwahati, India

[email protected]

[email protected]

[email protected]

Abstract— Injection molded long fiber thermoplastic

components are being used in recent days as a viable replacement

for metals in many applications .Present work focus on the effect

of fiber length on the short-term flexural creep performance of

fiber reinforced thermoplastic polypropylene. Unreinforced

polypropylene, 20 wt % short and 20 wt % long glass fiber

reinforced polypropylene materials was injection-molded into

flexural test specimens. Short-term flexural creep tests were

performed for 2 h duration on molded specimen at various stress

levels with the aid of in-house developed flexural creep fixture.

Experimental creep performance of polypropylene composites

for 2 h is utilized to predict the creep performance with the aid of

four parameter HRZ model and compared with 24 h

experimental creep data. Creep strain was found to be increased

with respect to time for all the test materials and found to be

sensitive with respect to the stress level. Test results also revealed

that long fiber reinforced thermoplastic material possessed

enhanced creep resistance over their counter parts and HRZ

model is sufficient enough to predict creep performance of

polypropylene composites over wide range of stress.

Keywords- Injection molding, flexural creep, thermoplastic,

creep, strain

I. INTRODUCTION

Due to the mass production requirement in the automotive

industries, discontinuous long fiber reinforced thermoplastics

(LFRT) have shown significant role in replacing metals, short

fiber reinforced thermoplastics, thermoset sheet molding and

bulk molding composites [1]. The common problem

associated with unreinforced thermoplastics is creep under

moderate to severe stress at elevated temperature. Creep

resistance of thermoplastic composites is significantly

improved by increase in fiber loadings [2]. Dynamic

mechanical analysis (DMA) was utilized to investigate the

viscoelasticity of injection-molded nylon 6/6 material

reinforced with short and long glass fibers by Sepe[3] and

reported an increase in creep resistance for long glass fiber

reinforced nylon composites. Challa and Progelhof [4]

investigated the effect of temperature on the creep

characteristics of polycarbonate and developed a relationship

based on Arrhenius theory to develop creep master curves.

Pegoretti and Ricco [5] studied the propagation of crack under

creep for varying temperature conditions for polypropylene

composites and observed that speed with which the crack

progresses was dependent on the test temperature.

Krishnaswamy [6] performed extensive creep rupture testing

on high density polyethylene pipes at various hoop stress

levels and temperatures and observed the dependency of

density and crystallinity towards failure. Houshyar [7]

reported the improvement in creep properties with the addition

of long polypropylene fibers in propylene-co-ethylene (PPE)

matrix and visualized the improvement in interfacial

properties. Trans-crystallization of the polypropylene matrix

was observed in the PPE samples due to the thin layer of

matrix on the reinforcement, which was attributed to good

impregnation and wetting of the fibers. Greco et al. [8]

investigated the flexural creep behavior for compression

molded glass fiber reinforced polypropylene at various applied

stress level. The effect of matrix crystallinity was highlighted

for the improvement in creep properties for glass fiber

reinforced polypropylene in their work. Acha et al. [9] studied

the influence of interfacial adhesion in discontinuous jute fiber

reinforced polypropylene. Relation between interfacial

properties and creep deformation were investigated. Higher

creep resistance was observed for polypropylene composites

with good interfacial bonding which was confirmed by the

observation of the composite fractured surfaces.

Findley and Khosla [10] conducted creep tests for

unreinforced thermoplastics; polyethylene, polyvinyl chloride

and polystyrene. Approximation was carried out for the linear

viscoelastic region by power law and compared the creep

performance by estimating the power law coefficient and

power law exponent. Liou and Tseng [11] used Findley power

law to estimate the creep compliance of carbon fiber nylon

composites in hygrothermal condition. Power law model was

modified by Hadid et al. [12] by incorporating the time and

stress dependence during creep loading of polyamide

specimens and estimated four parameters for describing the

deformation occurring in the material and used stress–time

superposition principle to predict long-term material creep

behavior of injection molded fiber glass reinforced polyamide.

mailto:[email protected]






Master curves were developed and a perfect

superposition of the curves at various stress levels was

visualized. Novak [13] used strain energy equivalence theory

and developed a creep predictive model to predict the creep

behavior of talc filled polypropylene. Banik et al. [14]

reported the improvement in creep resistance due to

unidirectional reinforcement for polypropylene-polypropylene

composites. Burger and Findley power law model were used

to predict the short term creep behavior and the underlying

deformation mechanisms were also investigated. Liu et al.

[15] used multi-Kelvin element theory and power law

functions to predict creep compliance in polyethylene material

and compared with the tensile creep experiments.

Even though a lot of works were carried out in the past

pertaining to the experimental creep behavior of plastics and

composites, estimation and prediction of creep data using

mathematical and numerical modeling is limited. Hence in this

work the influence of reinforced fiber length on the creep

performance of thermoplastic composite at various stress

levels at room temperature condition was carried out. The

results obtained through flexural creep test were analyzed

using Findley power law model and empirical model proposed

by Hadid et al [12]. Short term experimental creep results

were used to predict long term creep behavior of the molded

specimen.

II. THEORECTICAL BACKGROUND

A. Findley’s Power Law Model

Mechanical behavior of polymeric material under constant

stress was developed by Findley and Khosla [10]. The general

form of the power law equation is given as

' nt= ε tε(t) (1)

where ε(t) is the time dependent strain,'tε is power law

coefficient which is stress and temperature dependent

coefficient, n is the power law exponent and t is the time after

loading.Power law model is simple in approach and

successfully predicted nonlinear viscoelastic creep behavior of

thermoplastic composites over large range of stress[10-

13]besides

this model is also recommended by American

Society of Civil Engineers (ASCE) for structural plastics

design manual in the analysis of composite materials for long

term structural behavior [16].

B. HRZ Model

Findley’s power law was unsuccessful in accounting for the

stress effect on the mechanical behavior of polymeric

material. The two power law parameters in the Findley-Khosla

model'tε and n are significantly influenced by the applied

stress level. Hadid et al. [12] modified the Findley’s power

law to incorporate time and stress dependence in the model

where the power law coefficient (ε't) and power law exponent

(n) were plotted with respect to stress level (ζ). The best

fitting curve proposed the relation between '

tε and ζ as

( )ζb'ε =at (2)

Similarly the best fitting curve proposed between n and ζ

value takes the form

( )n=c exp e.ζ (3)

Eqs. (2) and (3) are used in eq. (1) and strain at any particular

time (t) can be calculated using the following HRZ equation

cexp(e.ζ)bε(t)= aζ t (4)

where a, b ,c ,e are the curve fitting parameters obtained

from the regression analysis. Chevali et al. [17] used the four

parameter HRZ model to fit the experimental data obtained

from flexural creep investigation for nylon 6/6, polypropylene

and high-density polyethylene based long fiber thermoplastic

composites.

III. EXPERIMENTAL CREEP PERFORMANCE OF

POLYPROPYLENE COMPOSITES

A. Specimen Fabrication

In the current investigation, 20 wt % short glass fiber

reinforced polypropylene (SFPP), 20 wt % long glass fiber

reinforced polypropylene (LFPP) and unreinforced

polypropylene (UFPP) obtained from Saint Gobain were used

for injection molding the specimens. In general, lengths of the

reinforced fibers in the short and long fiber reinforced pellets

are 1 mm and 12.5 mm respectively [18]. Weight average

fiber length of the reinforced fibers after injection molding for

the chosen SFPP and LFPP materials are 0.440 mm and 1.251

mm respectively [19]. The base resin of LFPP and SFPP

materials were having same molecular weight with a melt flow

index of 40 g/10 min. According to the material supplier’s

data, silane type coupling agent has been used for the

manufacturing of SFPP and LFPP materials. Since both the

investigated materials used the same type and amount of

coupling agent, material behavior discussions were limited

only to the reinforced fiber length. Developed injection

molding dies and molded specimens are shown in Figs 1a and

1b. Raw materials were initially preheated for two hours at

353 K and during molding, screw speed of 50 rpm and a low

back pressure of 0.25 MPa were kept to retain the residual

fiber length. Process parameters used for injection molding are

listed in Table I. Due to the presence of reinforced fibers in

LFPP and SFPP materials, temperature in the three zones were

kept higher than unreinforced material.




Fig 1a .Die for preparing specimens

Fig 1b. Injection molded specimens for flexural creep testing

TABLE 1

INJECTION MOLDING PARAMETERS FOR THE SPECIMENS

Screw diameter 35 mm

L/D 20

Screw speed 50 rpm

Barrel temperature

Zone 1

Zone 2

Zone 3

255 ο C

250 ο C

240 ο C

Injection speed 50 mm/sec

Mold temperature 40 ο C

IV. EXPERIMENTAL METHODOLOGY

A fixture is developed in house to evaluate the creep

performance of molded specimen according to ASTM D2990

standard. The specimen is kept in between the supports as

shown in Fig 2a and the load is applied at the centre of the test

specimen with the means of steel rod attached with dead load.

When the load is applied at the center the specimen is

deflected and the deflection is recorded in the dial gauge as

shown in Fig 2b. Test specimens were loaded with respect to

various stress levels for 2 hrs. Constant load is maintained and

test specimen deflection ( δ(t) ) is continuously measured and

recorded. Creep strain at instantaneous time ( )ε(t) is

computed using the relation (5) [20].

2

6δ(t).dε(t) =

l (5)

where, δ (t) is the deflection at instantaneous time , d is

the thickness and l the test specimen length. The

corresponding stress is calculated using the relation

max3Pl

S =2

2wd

(6)

Where Smax is the stress and P is the load, l is the length

and w is the width and d is the thickness of the specimen .The

length, width and thickness of the specimen is 70mm, 13 and

3mm respectively.

Fig 2(a-b). Assembled view of the flexural creep fixture

V. RESULTS AND DISCUSSIONS

A. Creep Behavior of Polypropylene Thermoplastic

Composites

Creep performance evaluation was carried out at various

loading levels ranging from 18.84 N/mm2 to 47.17 N/mm

2 for

all the materials. Fig 3 shows the 2h creep response of the

chosen test specimens. A raise in creep strain was observed

with the time period for all the specimens. Subsequent to the

preliminary rapid increase in creep strain, the rate of creep

Dial Gauge

Fixture

Steel Rod

Dead Weight

Specimen

Dial gauge

Reading

Fixture




strain decreases. Three trails were conducted for

calculating creep strain for all the molded materials and the

deviation for LFPP, SFPP and UFPP were found to be 2.5 %,

3.2 % and 1.5 % respectively Improved creep resistance

behavior of long fiber reinforced polypropylene is observed is

due to the improved load transfer from the matrix to the

reinforced fibers and the matrix constriction to deformation.

Chevali et al. [17] also observed a similar behavior with the

increase in loading of glass fiber reinforcement in the nylon

composites.

Fig 3. Comparison of creep strain for three materials for a stress of

22.5N/mm2

Due to the increase in reinforced fiber length, stiffness

retention is more pronounced in LFPP. Due to the substantial

time requirement for the creep investigation, an empirical

model is made use in the subsequent section to predict the

creep strain for a specific period of time.

B. Empirical Model for Predicting Short Term Creep

Behavior

The creep performance of molded specimens was

experimentally investigated for 2h duration for the stress

range varying from 18.84, 22.25, 38.27 and 47.17 N//mm2

and the test results are shown in Fig (4a-4c) .It is vivid from

the results that for all the tested materials, creep strain

increases with time and found to be increased with applied

stress level. Power law function is fitted using eq. (1) for each

and every stress levels thereby power law coefficient ('

tε ),

power law exponent (n) and correlation index (R2) are

determined.

Fig 4b. Creep strain for SFPP

The correlation index, R2 indicates that power law function

provides a good approximation to the visco elastic behavior at

every stress levels. It is vivid from Figs (4a-4c) that the power

law coefficient ('tε ) and power law exponent (n) are

dependent on the stress level and increases with the increase in

stress level

Since the power law coefficient ('tε ) and power law exponent

(n) are sensitive to the stress level, a methodology adopted by

Hadid et al.[12] was used to establish the dependence of

power law coefficient ('tε ) (Fig5a) and power law exponent

(n) (Fig 5b) on applied stress level. Fig 5a shows the best

fitting curve using eq. (2) and depicts the influence of applied

stress (ζ) on power law coefficient ('tε ) for the test specimen .

The constant curve fitting parameters (a, b from eq. 2) are also

shown in Fig 5a. In general the constant parameters a and b

are dependent on glass transition temperature, degree of

crystallinity, and fiber orientation in the composite[20] . These

parameters represent the instantaneous strain normally

visualized during the initial period of load application. Fig 5b

shows the best fitting curve using eq. (3) and elucidates the

influence of applied stress (ζ) on power law exponent (n) for

the test specimen. The constant curve fitting parameters (c, e

from eq. 3) are also shown in Fig 5b. The constant parameters

c and e are dependent on the time period of testing and

relaxation mechanisms involved for the composite. These

parameters represent the viscous response visualized during

the secondary creep process. Eq. (4) is used to predict creep

performance of molded specimen and compared with the 24 h

experimental data as shown in Fig 6 (a-c). It is found that HRZ

model predicted well with the experimental creep performance

of the chosen thermoplastic composite specimen.




Fig 4c. Creep strain for LFPP

Fig 5a. Variation of power law coefficients over stress

Fig 5b. Variation of power law exponents over stress

Fig 6a Experimental and predicted creep performance of UFPP for 55MPa

Fig 6b Experimental and predicted creep performance of SFPP for 40MPa

Fig 6c Experimental and predicted creep performance of LFPP for 20MPa




VI. CONCLUSIONS

Discontinuous fiber reinforced polypropylene composites

were injection molded and its short term flexural creep

performance is investigated. Due to the extensive time

requirement for the creep performance evaluation, HRZ model

was used in this work. Creep performance of the molded

specimens was experimentally evaluated for 2 h and short

term creep performance (24 h) was predicted with the aid of

HRZ model over wide range of stress. The predicted

performance was compared with 24 h experimental results and

found to be satisfactory. From the present investigation, HRZ

model was found to be useful in predicting the short-term

creep performance of viscoelastic engineering material.

Experimental results confirmed that long fiber reinforced

thermoplastics possessed enhanced creep retention

characteristic. HRZ model parameters were also utilized to

correlate investigated material characteristics.

REFERENCES

[1] J. Markarian, “Long fibre reinforcement drives

automotive market forward”, Plastics, Additives and

Compounding, Vol.7, pp.24-29, 2005.

[2] B.V. Gupta and J. Lahiri, “Non-linear viscoelastic

behavior of polypropylene and glass reinforced

polypropylene in creep,” Journal of Composite

Materials, Vol.14, pp.288-296, 1980.

[3] Sepe, M.P. Use of advanced characterization

techniques in evaluating the fitness-for-use of long-

glass fiber thermoplastics: San Francisco, 1994,

pp.2029-2032.

[4] S.R .Challa and R.C .Progelhof, “A study of creep

and creep rupture of polycarbonate”, Polymer

Engineering and Science, Vol.6, pp.546-554, 1995.

[5] A. Pegoretti and T.Ricco, “Creep crack growth in a

short glass fibres reinforced polypropylene

composite”, Journal of Material Science, Vol.19,

pp.4637-4641, 2001.

[6] R.K. Krishnaswamy, “Analysis of ductile and brittle

failures from creep rupture testing of high-density

polyethylene (HDPE) pipes”, Polymer, Vol. 28,

pp.11664 -11672, 2005.

[7] S.Houshyar , R.A.Shanks and A. Hodzic, “Tensile

creep behavior of polypropylene fibre reinforced

polypropylene composites”, Polymer Testing,Vol.

24,pp. 257-264,2005.

[8] A.Greco, Claudio Musardo and Alfonso Maffezzoli,

“Flexural creep behaviour of PP matrix woven

composite”, Composites Science and Technology,

Vol.67, pp.1148-1158, 2007.

[9] B.A. Acha M.M.Reboredo, and N.E.Marcovich,

“Creep and dynamic mechanical behavior of PP–jute

composites: Effect of the interfacial adhesion”,

Composites Part A: Applied Science and

Manufacturing, Vol.33, pp.1507-1516, 2007.

[10] W.N. Findley and G. Khosla, “Application of the

superposition principle and theories of mechanical

equation of state, strain, and time hardening to creep

of plastics under changing loads”, Journal of Applied

Physics, Vol.26, pp.821–832,1955.

[11] W.J. Liou and C.I. Tseng, “Creep behavior of nylon-

6 thermoplastic composites”, Polymer Composites,

Vol.18, pp.492-499, 1997.

[12] M.Hadid, S.Rechak and A.Tati, “Long-term bending

creep behavior prediction of injection molded

composite using stress-time correspondence

principle”, Materials Science and Engineering A,

Vol.385, pp.54-58, 2004.

[13] G.E. Novak, “Creep fracture of long fiber reinforced

nylon 66”, Polymer Composites, Vol.16, pp.38-51,

1995.

[14] K.Banik, J.Karger-Kocsis and T. Abraham, “Flexural

creep of all-polypropylene composites: Model

analysis”, Polymer Engineering Science, Vol.48,

pp.941-948, 2008.

[15] H.Liu, M.A.Polak and A.Penlidis, “A practical

approach to modeling time-dependent nonlinear

creep behavior of polyethylene for structural

applications”, Polymer Engineering Science, Vol.48,

pp.159-167, 2008.

[16] American Society of Civil Engineers, Structural

Plastic Design Manual, 1986.

[17] V.S.Chevali, D.R. Dean, and G.M. Janowski,

“Flexural creep behavior of discontinuous

thermoplastic composites: Non-linear viscoelastic

modeling and time–temperature-stress

superposition”, Composites: Part A, Vol. 40, pp. 870-

877, 2009.

[18] “Twintex Product Data Sheet”, Long fiber

thermoplastic pellets, 2005, USA.

[19] C.Subramanian and S.Senthilvelan, “Development

and preliminary performance evaluation of

discontinuous fiber reinforced thermoplastic leaf

spring”, Journal of Materials: Design and

Applications, Proc. of Ins. Mech. E Part L,Vol.

223(3), pp.131-142, 2009.

[20] “ASTM D-2990 Standard test methods for tensile,

compressive, and flexural creep and creep-rupture of

plastics”, ASTM International, Philadelphia.

http://www.sciencedirect.com/science/journal/1464391X


http://www.springerlink.com/content/?Author=A.+Pegoretti

http://www.springerlink.com/content/?Author=T.+Ricco

http://www.sciencedirect.com/science/journal/00323861



International Journal of Students‟ Research in Technology & Management



E-Waste: An Emerging Problem of

Innovative Society

Rahila N. Gadi#1

, Nabeel Ahmed N.Gadi*2

#Dept of E&CE-Al-Musanna’s College of Technology, Oman

*Dept of Community Medicine MM institute of Medical Science &Research Mullana, Haryana, India

[email protected]

[email protected]

Abstract– In the past few years there is a revolution in electronic

industry, which increases the volume and varieties of both solid

and hazardous wastes. Urbanization Industrialization, fast

changes in technologies leave a negative impact on health of

human beings. Also increases the pollution in air, land and

water. A growing municipal waste contains hazardous electrical

and electronics products. When dumped in landfill will pollute

the environment badly. This waste is usually named as E-waste

(Electrical an Electronics Waste).In the absence of suitable

techniques and protective measures, recycling e-waste can result

in toxic emissions to the air, water and soil and pose a serious

health and environmental hazard-waste is assuming serious

proportions in developing countries and urgent steps need to be

taken to mitigate this problem. This paper highlights the

problem posed by e-waste and its hazards on environment and

health

Keywords– E-waste (Electrical &Electronic waste), carcinogen,

landfills

I. INTRODUCTION

During the last few years, there is an increasing

acknowledgment of our impact on the environment due to our

lifestyle, while the need to adopt a more sustainable approach

concerning our consumption habits emerges as of particular

significance. This trend regards industrial sector affecting the

consumption habits and especially electronic industry where

the short life cycles and the rapidly developing technology

have led to increased E-waste volume [3]

Electrical and Electronics waste, also known as Electronic

waste or waste electrical & electronics equipment (WEEE), or

in short called E-waste, is used to describe obsolete or end of

life electrical & electronics equipment [4]. There is no

generally accepted definition of E-waste around the

world[2].According to the European Union directive WEEE

means Electrical or Electronic Equipment which is waste

within the meaning of article1(a) of directive75/442/EEC

,including all components, subassemblies and consumables

which are part of the product at the time of discarding

.However E-waste most often misunderstood as comprising

only computers related IT equipment or email spam[5].It is

universally understood as electronic waste disposed of by end

users and a wide range of products, from simple devices to

complex goods .Therefore E-waste comprises both white

goods such as refrigerators ,washing machines and

microwaves ,and brown goods which consists of TV ,Radios

and Computers that have reached their ends for their current

holder[6].

E-waste mainly comes from several sources:

Residue or leftover materials from electronic

products manufacturing process

.Leftover parts or materials or discarded EEE

generated from a repair shop

Obsolete EEE coming from all sector of society like

government offices, Companies, Education institutes,

Household etc

Obsolete electrical or electronic products brought in

by smuggling [7].

The production of electrical & electronic equipment (EEE)

is one of the fastest growing global manufacturing activities.

Rapid economic growth, coupled with urbanization and a

growing demand for consumer goods has greatly increased

both the consumption and the production of EEE [8][9][10]

II. MAGNITUDE OF PROBLEM

The magnitude of the problem is really huge and scary.

According to UNEP, global E-waste generation is growing by

about 40 million tons a year, and predicts that by 2020 in

South Africa & china E-waste from old computers will jump

by 200 to 400% from 2007 levels and by 500% in India

[2].Developing countries are the major dumping grounds for

E-waste. By 2020 there will be increase by 400 to 500%.The

spectrum of hazardous E-waste Mountain looms large

especially for developing countries with serious consequences

for the environment and public health[11].The global E-waste

production is accessed at 20-50 million ton/year, equal to 1-

3% of the estimated global urban waste production. Personal

computers, Cell phones and TV will contribute 5.5 Mt in 2010

and will increase to 9.8Mt in 2015.In developed countries E-

waste will stand for 8% of the urban waste volume[3].Each





item‟s participation in the annual E-waste

production(kg/year),depends on each electronics‟ item‟s mass

M(Kg),its quantity (number) in the market and

consumption(N) and its Average life cycle L (year).

Estimated Life E = MN/L

For computers with an average 3 years life cycle

contributes to a greater extent to the total E-waste flow

compared to refrigerators and electric stoves, having an

average of 10-12 years [12].Certain electrical & electronics

equipment‟s which form the major part of the E-waste

generation along with their mass and estimated life cycle are

summarized in Table 1.

TABLE 1

ELECTRICAL & ELECTRONICS EQUIPMENTS & THEIR ESTIMATED

LIFE

Items Mass(Kg) Estimated Life(Yrs)

Personal Computer 25 3

Cell Phones 0.1 2

Television 30 5

Fax Machines 3 5

AC 55 10

Photo copier 60 8

Washing Machine 65 8

Refrigerator 35 10

Microwave 15 7

Vacuum Cleaner 10 10

III. IMPACT ON HEALTH & ENVIRONMENT

E-waste cannot be considered or treated like any kind of

waste, because it contains hazardous and toxic substances

such as heavy metals or others such as dioxins and furans

(produced when E-waste is incinerated).For instance, lead

represent 6% of the total weight of a computer monitor. It is

been reported that nearly 36 chemical elements are

incorporated in electronic equipment‟s [13].Electronic wastes

can cause widespread environmental damage due to the use of

toxic materials in the manufacture of electronics goods.

Hazardous metals such as lead (Pb) ,Mercury(Hg) and

hexavalent chromium[Cr(VI)],in one form or the other are

present in such wastes primarily consisting of cathode ray

tubes(CRTs),PCB, capacitors, mercury switches ,relays

.batteries etc. Liquid Cr tetardants on PCB, LCD, cartridges

from photocopying machines, selenium drums etc. Land

filling of E-waste can lead to the leaching of lead (Pb) into the

groundwater and leads to un-portability of water. If the CRT

is crushed and burned, it emits toxic fumes into the air cause

air pollution, which are very hazardous to human being as

well as animals. A rechargeable battery which contains toxic

substances that can contaminate when burned in incinerators

or disposed of in landfills .E-waste is much more hazardous

than many other municipal wastes. Long term exposure to

these substances damages the nervous system, kidney,

reproductive system, endocrine system and bones. It also

leads to carcinogen (cancer).Workers in E-waste recycling or

disposal sector are poorly protected against the risk of it. They

dismantle E-waste, often by hand in very unhealthy

conditions. The hazardous substances found in the E-waste

are considered dangerous to health. Inhaling or handling such

substances and being in contact with them on a regular basis

can damage the main organs of the human body. Working in

poorly-ventilated enclosed areas without masks and technical

expertise result in exposure to dangerous and slow poisoning

chemicals. Due to lack of awareness, workers are risking their

health [15][14].Scientist who examined Guiyu, China(one of

the popular destinations of E-waste recycling activities) have

determined that because of waste, the location has the highest

level of cancer causing dioxins in the world. Pregnant women

are six times more likely to suffer a miscarriage, and seven

out of ten kids have too much lead (Pb) in their blood [17]. E-

waste is not alone factor in causation of environmental and

health problems but its inadequate management which plays

as a catalyst in the magnitude of the problem.

IV. STRATEGIES FOR REDUCTION OF E- WASTE

The best option for dealing with E-waste is to reduce the

volume. Designers should ensure that the product is built for

re-use and/or upgradability. Stress should be laid on use of

less toxic, easily recoverable and recyclable materials which

can be taken back for refurbishment, remanufacturing,

disassembly and reuse. Recycling and reuse of material are

the next level of potential options to reduce E-waste.

Recovery of metals, plastic, glass and other materials reduces

the magnitude of E-waste. These options have a potential to

conserve the energy and keep the environment free of toxic

materials that would otherwise have been released. It is high

time the manufactures, consumers, regulators, municipal

authorities and policy makers take up the matter seriously so

that the different critical elements are addressed in an

integrated manner. It is need of the hour to have an “E-waste

policy “and national regulatory framework for promotion of

such activities. An E-waste policy is best created but those

who understand the issues. So it is best for industry to initiate

policy formation collectively, but user involvement.

Sustainability of E-waste management system has to be

ensured by improving the effectiveness of collection and

recycling system (e.g: public-private partnership in setting up

buy back or drop off center) and by designing in advance

funding [1][15].The E-waste generated every year globally is




40-50 million ton out of which 15 to 20 % is

recycled and remaining is dumped in landfills/incinerators. If

we have a good and effective recycling system and good

policies to carry recycling process than we can sustain our

natural resources which is depleting very fast

V. E-WASTE MANAGEMENT

To have a better management of E-waste the end user

should be aware of the hazardous affects of E-waste. Proper

awareness should be given and in turn survey should be

conducted to find what people are doing with their E-waste. Is

they are just dumping in the store room or selling to scrap

people or they are giving back to the company .Find the

amount of E-waste generated, by surveys from all sector of

society, awareness program to educate the people how to

reuse the existing Electrical & Electronics products. Next step

will be the design of a proper E-waste management system to

reduce and to recycle the E-waste generated. The first in the

process is to collect the E-waste from all sector of the society

i.e from companies, institution, residential, hospitals etc.

The second step involved to manage the E-waste is to

apply the principle of three R i.e. Reduce, Reuse and Recycle.

As the duty of the user is that try to minimize the E-waste

generation by up grading the system or repair it. If those

things will not give the expected output then try to resale or

recycle it. Many companies have take back schemes.

Segregation & dismantling of the various equipment or

components is the third step where under proper environment

this process is carried out. In the recycling process we can

recovery many valuable materials and metals. Which can be

reused? The last part is the hazardous materials disposal that

has to be done with at most cares.[1][2][16]

VI.NEED FOR E-WASTE POLICY AND REGULATION

The policy should address all issues ranging from

production and trade to final disposal, including technology

transfer for the recycling of electronics waste. Clear

regulatory instruments, adequate to control both legal or

illegal exports and imports of E-waste and ensuring their

environmentally sound management should be in place.

According to the EU the designers and the manufactures have

to obey the RoHS directive which bans or restrict the use of

certain hazardous substances like lead and its compound,

Cadmium and ,its compound, Mercury, hexavalent chromium,

polybrominated biphenyls[1].The regulations should prohibit

the disposal of E-waste in municipal landfills and encourage

owners and generators of E-waste to properly recycle the

waste. Manufactures of products must be financially,

physically and legally responsible for their products. Better

management of hazardous substances may be implemented

through measures such as

Specific product take back obligations for industry.

Financial responsibility for actions and schemes

Greater attention to the role of new product design.

Follow RoHS directives.

Greater scrutiny of cross border movements of

electrical & electronic products and E-waste

Increasing public awareness by labeling products as

“Environmental Hazard”

Personal protection measures (masks, Gloves,

shields, protective glasses etc) should be made

available to all the workers who are engaged with E-

waste management.

The key questions about the effectiveness of legislation

would includes

What is to be covered by the Term Electronic Waste

Who pays for disposal is the producer responsibility

the answer.

What would be the benefits of voluntary

commitments

How can sufficient recovery of materials be achieved

to guarantee recycling firms a reliable and adequate

flow of secondary materials [18].

A. Benefits of E-Waste

Conservation of natural resources

Preventing soil, water and air contamination by toxic

chemicals.

By back offers for consumers

Creates new jobs in the market

Creates new markets for secondary materials and

components

B. Energy Efficiency [19][16]

Reduction of energy requirement, cost involved in E-

waste recycling is comparatively less than the cost involved in

mining and processing of new materials from scratch.

Recycling of Aluminum can save 95% of energy than

production from basic ore. Recycling of plastic can save 70%

of energy and glass up to 40%.Recovering of metals from

recycling process generates only a fraction amount of co2

emission compared from natural process. Innovation in E-

waste treatment should focus on the major needs to improve

overall sustainability [1][18].Some of the policies in place

globally for effectively managing E-waste are mention in

table 2.




TABLE 2

REGULATORY MODEL

Producers

Responsibility

Government

Responsibility

Model Commonly known

as EPR

Manufacturers

financially

responsible beyond

point of sale. Take back Schemes &

recycle them up to

a defined

percentage by the

manufacturers

Funding model for

this activity varies

from company to

company

End consumer

taxed a recycling

fee on the

purchased product.

This Tax/Fees is

used to fund the E-

waste collection &

recycling activity

Government is

responsible to

monitor & collect

the E-waste

Current Examples European Union

Japan, South

Korea, Taiwan

Switzerland

California(USA)

Likely Implications Pressure on

manufacturers to

follow RoHS

directive

No incentives for

manufacturer to

create cleaner

design.E-waste not

likely to reduce as

manufacturers do

not have any

liability

VII. CONCLUSION

The Electronic market has revolutionized the whole world

over last decades as Electrical & Electronics products

increasingly capture the major part of our lifestyle. While no

one can give the exact figures how much E-waste is presently

generated or how much of this is hazardous, what is definite is

that if we the people living in the innovative society don‟t try

to manage the E-waste properly then E-waste have the

potential of threatening human health and its environment.

Initiatives are been taken to reduce the volume of generation

and to have an effective recycling techniques, which can

sustain the natural resources as well as conserve the energy.

E-waste in developing countries is a menace. There is lack of

awareness among the people about E-waste. This paper

highlights some of the problems, their impact on human

health and environment, briefly explains how to have an

effective E-waste management system with examples

REFERENCES

[1] Dejo Olowu Article „Menace of E-Wastes in

Developing CountriesAn Agenda for Legal and Policy

Responses‟, Lead Journal-ISS1746-58938/1 Law,

Environment and Development Journal (2012), p.59,

available at http://www.lead-

journal.org/content/12059.pdf

[2] Sustainable Innovation & Technology Transfer

Industrial Sector studies Recycling from E-waste to

resources, July 200 UNEP-STEP

[3] G. Gaidajis*, k. Angelakoglou and d. Aktsoglou, e-

waste: environmental problems and current

management, journal of Engineering science and

technology review 3 (1) (2010) 193- 199

[4] Y. C. Jang and h. Yoon, 2006. The practice and

challenges of electronic waste recycling in korea with

emphasis on extended producer responsibility (EPR).

Anweshaborthaku, pardeepsingh international journal of

environmental sciences volume 3 no.1, 2012

[5] Deepalisinhakhetriwal, philippkraeuchi, rolfwidmer,

2007. Producer responsibility for ewaste management:

key issues for consideration – learning from the swiss

experience.Journal of environmental management,

2007. Xx: 1–1

[6] Shah alam, selangor, electrical and electronic waste

management practice by households in , malaysia,2010,

international journal of environmental sciences volume

1, no 2 ,2010

[7] Ramesh babu b, parandeak, ahmedbasha c. Electrical

and electronic waste: a global environmental problem.

Waste manag res. 2007;25:307–18. [pubmed].

[8] Sinha s. Downside of the digital revolution. Published in

toxics link, 28/12/2007. Accessed 13 feb/96/ec . 2013.

Available: http://www.toxicslink.org/art-

view.php?id=124

[9] V. O. Akinseye, electronic waste components in

developing countries: harmless substances or potential

carcinogen, 2013, annual review & research in biology,

3(3): 131-147 , 2013

[10] Bina rani et al, j advscient res, 2012, 3(1): 17-21 17

[11] K. Betts, producing usable materials from e-waste,

environ sci technol. 42, pp. 6782–6783 (2008)

[12] Musson se, jangnyc, townsendtg, chungih.

Characterization of lead leachability from cathode ray

tubes using the toxicity characteristic leaching

procedure. Environmental science & technology.

2000;34(20):4376-4381

http://www.lead-/




[13] Ajeetsaojie-waste management: an emerging

environmental and health issue in india,national journal

of medical research,volume 2 issue 1 jan – march 2012

issn 2249 4995

[14] India together: un report spotlights india‟s e-waste pile

up – 31 march 2010. Available from:

http://www.indiatogether.org/2010/mar/env-

unewaste.htm

[15] Electronic waste: where does it go and what happens to

it? By michellecastillo: january 2011. Available from:

http://techland.time.com.

[16] Environment, energy and transportation program;

electronic waste. National conference of state

legislatures [cited june 10, 2006]; available from

http://www.ncsl.org/programs/environ/cleanup/

elecwaste.

[17] Waste wise update: electronics reuse and recycling.

Environmental protection agency 2000 [cited july 14,

2006]; available from: http://

www.epa.gov/wastewise/wrr/updates.htm.

[18] Article on Benefits of E-waste Recycling by Drew

Hendricks in Growing Green Jobs August 6, 2012

Available from www.ewaste.htm

http://techland.time.com/

http://www.ncsl.org/programs/environ/cleanup/elecwaste

http://www.ncsl.org/programs/environ/cleanup/elecwaste

http://www.epa.gov/wastewise/wrr/updates.htm

http://www.ewaste.htm/




Trend Analysis of Climate Variability in Salalah,

Oman Mohammed Al-Habsi

#1, Luminda Gunawardhana

#2, Ghazi Al-Rawas

#3

# Department of Civil and Architectural Engineering, Sultan Qaboos University

P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman 1 [email protected]

2 [email protected]

3 [email protected]

Abstract—The frequency and intensity of weather events are

expected to change as climate change, which may result in more

frequent and intensive disasters such as flash floods and

persistent droughts. Subsequent impacts will affect regions in

different ways, but projected to worsen conditions in water

scares countries like Oman. In Oman, changes in precipitation

and temperature have already begun to be detected, although a

comprehensive analysis to determine long-term trends has yet to

be conducted. We analyzed daily precipitation and temperature

records in Salalah city of Oman, mainly focusing on extremes. A

set of climate indices, defined in the RClimDex software package,

were derived from the longest available daily series (precipitation

over the period 1943-2011 and temperature over the period 1991-

2011). Results showed significant changes in daily minimum and

maximum temperatures associate with cooling as well as

warming. The annual number of cold nights (percentage of days

when daily minimum temperature (TN) less than 10th percentile

of that during base period: 1991-2000) decreased by 8 days per

decade (p-value = 0.3). On the other hand, the annual number of

warm nights (percentage of days when daily minimum

temperature (TN) larger than 90th percentile of that during base

period) increased by 10 days per decade (p-value = 0.3). In

contrast, the annual occurrence of cold days increased by 11 days

per decade (p-value = 0.25), while the annual occurrence of warm

days decreased by 4 days per decade (p-value = 0.62). The

significant trends apparent in minimum temperatures reveal that

Salalah area has become less cold rather than hotter. Moreover,

contrary trends in minimum and maximum temperatures

indicate that, in long-term, daily temperature range has

decreased in this area.

Annual total precipitation averaged over the period 1943-2011

is 95 mm, which shows a statistically weak negative trend with a -

2 mm/10 yr rate. There is also a tendency for precipitation

extremes according to many indices. The contribution from very

wet days to the annual precipitation totals steadily increases with

significance at 87% level. The positive trend in simple daily

intensity index is also clear and reasonably significant (p-value =

0.29). Results of all these indices lead us to conclude that

precipitation intensity in Salalah has increased while mean

precipitation changes are less marked.

I. INTRODUCTION

Extreme weather events are causing extensive damage to

economy, environment and human life. For example, the

supper cyclone, hurricane gonu in 2007 caused extensive

damage along coastline cities, with total rainfall reached 610

mm near the coast. The cyclone caused about 4 billion in

damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008).

Many studies show that these extreme events that used to be

rare in more than 60 years before are becoming frequent in

many parts of the world in recent decades. Alexander et al.

(2006) assessed changes in daily temperature and precipitation

extremes. They found that the trends in minimum temperature

are more significant, implying that many regions become less

cold rather than hotter. Easterling et al. (2000) revealed the

heavy precipitation change in Siberia and northern Japan

while mean precipitation changes are less marked. Therefore,

greater understanding of occurrence of past extremes is prime

important to avoid or at least to reduce the damages such as

catastrophic floods and prolonged period of droughts

(Beniston et al. 2007; Fowler et al. 2005).

In Oman, changes in precipitation and temperature have

already detected (Al Rawas and Valeo, 2010), although a

comprehensive analysis to determine long-term trends has yet

be conducted. With efforts to build a long-term database, the

Sultan Qaboos University now possessed quality controlled

records of daily temperature over the period 1991-2011 and

daily precipitation over the period 1943-2011. The objective

of this research is to use these data to evaluate the trends of

extreme temperature and precipitation change in Salalah.

II. STUDY AREA

Salalah, the second largest city in the Sultanate of Oman,

located in southern of Oman and on the edge of the Indian

Ocean (Fig. 1). Annual total precipitation averaged over the

period 1943-2011 is 95 mm, which shows statistically weak

negative trend of a 2 mm/10-years. Mean annual temperature

during 1980-2008 warms at a rate of 0.12°C/10-years, which

is relatively small compared to warmings recorded in northern

cities such as Sur and Khasab (1.03 and 0.5°C per decade,

respectively). Salalah costal plain serves one of the intense

agricultural fields in the Sultanate of Oman. Consequently,

over the time, saline water intrusion has become one of the

major issues for the management of sustainable groundwater

resource. By the end of 2003, a main project was operated to

treat wastewater and re-inject 20000 m3 daily in the coastal

wells in Salalah in order to stop seawater intrusion. In past,

severe cyclones have occurred in Salalah area in 1959, 1963





and 1966. In 2002, a tropical storm affected Salalah

city which brought 58.6 mm rain in the city area and 250.6

mm rain in adjoining mountains.

Fig. 1. Study area in Oman

III. METHODOLOGY

In this study, maximum and minimum temperatures, and

precipitation trends were analysed using a selection of 27

indices. These indices were calculated using RClimDex

software, which was developed by the Expert Team on

Climate Change Detection, Monitoring and Indices

(ETCCDMI) to analyse many aspects of a changing climate

(Alexander et al. 2006). The quality control procedure in

RClimDex was applied to identify errors in data processing.

Both minimum and maximum daily temperatures were

considered as missing values if daily minimum temperature is

greater than daily maximum temperature. Daily maximum and

minimum temperature records were defined as outliers if they

lye outside the range of four standard deviations (STDEV)

from the mean of the records (Mean ± 4 × STDEV). Negative

precipitation records were also considered as missing values.

Homogeneity test was conducted using RHtest software

package to identify abrupt changes in data series. However, no

artificial step changes were detected.

IV. RESULTS AND DISCUSSION

The set of 27 indices used in this study includes 16

temperatures related and 11 precipitation related indices

which describe changes in intensity, frequency and duration of

temperature and precipitation events. For space reason, we

present specific indices with significant impacts, together with

combined indices, if the thresholds represent to values of

hydrological significance. A trend is said to be detected when

a test of the null hypothesis that no trend is present is rejected

at a high significance level, such as 5% or 10%.

We found no significant changes in most of precipitation

indices (Table 1). However, consecutive wet days (CED)

shows negative trend with a confidence 89% (Fig. 2). On the

other hand, consecutive dry days (CDD) increases but exhibits

only a statistically weak relationship with standard error larger

than the slope of the fitted linear regression line. The simple

TABLE I

TEST STATISTICS OF PRECIPITATION INDICES

Index Slope Standard

error P-value

Significant at

5% 10%

CDD 0.253 0.38 0.507 No No

CWD -0.031 0.020 0.113* No No

PRCPTOT -0.194 0.535 0.718 No No

RX1day 0.018 0.211 0.933 No No

RX5day -0.157 0.284 0.581 No Yes

R95P 0.153 0.466 0.744 No No

R95P/

PRCTOT 0.0027 0.0017 0.130* No No

SDII 0.015 0.014 0.285 No No *Significance level < 25%

Fig. 2. Trend of consecutive wet days (CWD)

Fig. 3. Trend of simple daily intensity index (SDII)

Salalah




Fig. 4. Contribution from very wet days to total precipitation

daily intensity index (SDII), which is the ratio of annual

precipitation and number of wet days, shows a reasonably

positive trend with a confidence of 71% (Fig. 3). Figure 4

depicts that the contribution from very wet days to the annual

precipitation total steady increases with a reasonable high

confidence of 87%. In other words, the probability of the null

hypothesis (no contribution from extreme precipitation)

becomes true is less than 0.13. These results lead us to

conclude that precipitation intensity in Salalah has increased

while the annual total precipitation slightly decreases.

Both absolute temperature indices: TNn (annual minimum

value of daily minimum temperature) and TXx (annual

maximum value of daily maximum temperature) in Table II

exhibit no statistically significant change. However, the trends

of TNx (annual maximum value of daily minimum

temperature, Fig. 5) and TXn (annual minimum value of daily

maximum temperature, Fig. 6) are relatively significant. The

absolute magnitude of the gradients of two curves is higher

than standard errors, even though none of them are

statistically significant at 10% level. The extreme temperature

range (ETR) index calculated from the difference between

TXn and TNx indicates a reasonably strong upward trend (Fig.

7) with a confidence of 86%. In practical point of view, these

changes indicate that the temperature of warmest nights

increases while the temperature of coolest day times decreases.

When the percentile based indices were considered, the annual

number of cold nights (percentage of days when daily

minimum temperature (TN) less than 10th

percentile of that

during base period: 1991-2000) decreased by 8 days per

decade (p-value = 0.3). On the other hand, the annual number

of warm nights (percentage of days when daily minimum

temperature (TN) larger than 90th

percentile of that during

base period) increased by 10 days per decade (p-value = 0.3).

In contrast, the annual occurrence of cold days increased by

11 days per decade (p-value = 0.25), while the annual

occurrence of warm days decreased by 4 days per decade (p-

value = 0.62).

V. CONCLUSIONS

In this study, precipitation and temperature extremes in

Salalah, Oman were investigated using a set of climate indices.

The significant trends apparent in minimum temperatures

reveal that Salalah area has become less cold rather than hotter.

Moreover, contrary trends in minimum and maximum

temperatures indicate that, in long-term, daily temperature

range has decreased in this area.

Many precipitation indices show no statistically significant

trend. However, there is a tendency for precipitation extremes

according to some indices. The contribution from very wet

days to the annual precipitation totals steadily increases with a

confidence of 87%. The positive trend in simple daily

intensity index is also clear and reasonably significant (p-

value = 0.29). However, the annual total precipitation

averaged over the period 1943-2011 shows a weak negative

trend with a -2 mm/10 yr rate. Results of all these indices lead

us to conclude that precipitation intensity in Salalah has

increased while mean precipitation changes are less marked

TABLE III TEST STATISTICS OF TEMPERATURE INDICES

Index Slope Standard

error

P-

value

Significant at

5% 10%

TNn -0.016 0.027 0.562 No No

TXx -0.077 0.105 0.472 No No

TNx 0.024 0.024 0.338 No No

TXn -0.056 0.052 0.299 No No

CSDI -0.353 0.270 0.206* No No

DTR -0.02 0.008 0.025* No No

TN10P -0.217 0.202 0.296 No No

TN90P 0.282 0.266 0.302 No No

TX10P 0.313 0.265 0.253 No No

TX90P -0.120 0.239 0.622 No No

ETR 0.079 0.051 0.137* No No *Significance level < 25%

Fig. 5. Trend of annual maximum value of daily minimum temperature (TNx)




Fig. 6. Trend of annual minimum value of daily maximum temperature (TXn)

Fig. 7. Trend of extreme temperature range index (ETR)

ACKNOWLEDGMENT

Authors wishes to acknowledge Prof. Xuebin Zhang and

Prof. Feng Yang at the Climate Research Branch of

Meteorological Service of Canada for providing RClimDex.

REFERENCES

[1] M. E. Rafy, and Y. Hafez, ―Anomalies in meteorological

fields over northern Asia and its impact on Hurricane

Gonu,‖ 28th

Conference on Hurricanes and Tropical

Meteorology, pp. 1–12, 2008.

[2] L. V. Alexander, et al., ―Global observed changes in

daily extremes of temperature and precipitation,‖

Journal of Geophysical Research, 111, D05109,

doi:10.1029/2005JD006290, 2006.

[3] D. R. Easterling, T. R. Karl, K. P. Gallo, D. A. Robinson,

K. E. Trenberth and A. Dai, ―Observed climate

variability and change of relevance to the biosphere,‖

Journal of Geophysical Researches vol. 105, pp. 101–

114, 2000.

[4] G. A. Al-Rawas and C. Valeo, ―Relation between Wadi

drainage characteristics and peak flood flows in arid

northern Oman,‖ Hydrological Sciences Journal,vol. 55,

pp. 377-393, 2010.

[5] M. Beniston et al., ―Future extreme events in European

climate: an exploration of regional climate model

projections,‖ Climatic Change, vol. 81, pp. 71–95, 2007.

[6] H. J. Fowler, M. Ekstrom, C. G. Kilsby and P. D. Jones,

―New estimates of future changes in extreme rainfall

across the UK using regional climate model integrations,

1. Assessment of control climate,‖ Journal of Hydrology,

vol. 300, pp. 212–233, 2005.




Using a New Programme to Predict Thermal

Comfort as a Base to Design Energy Efficient

Buildings

Hanan Al-Khatri # ¹, Mohamed B. Gadi*²

# Civil and Architectural Engineering Department, Sultan Qaboos University, Oman

* Department of Architecture and Built Environment, University of Nottingham, UK

¹[email protected]

²[email protected]

Abstract---- A strong relationship relates the thermal comfort and

the consumption of energy, especially in the hot arid climate

where the installation of HVAC systems is unavoidable. In fact, it

has been reported that the HVAC systems are responsible for

consuming huge amounts of the total energy used by the

buildings that can globally reach up to 40% of the total primary

energy requirement. The future estimations indicate that the

energy consumption is likely to continue growing in the

developed economies to exceed that of the developed countries in

2020. Under these situations, it seems that the shift towards more

energy efficient buildings is not an option. Because part of any

successful environmental design is to understand the potentials of

the site, the proposed programme (THERCOM) assists in

weighing the indoor and outdoor thermal comfort in different

climates in order to provide better understanding of the site

environment as well as testing the thermal comfort chances of the

initial concepts.

Keywords---- energy efficient buildings, indoor thermal comfort,

outdoor thermal comfort, passive design, arid climate, equatorial

climate, warm temperate climate

I. INTRODUCTION

The current records indicate that the buildings sector is

responsible for consuming 40% approximately of the total

primary energy requirements [1]. For any typical building,

around 80% of this amount is consumed as an operational

energy from which huge amounts are consumed for the

HVAC systems alone [2]. This pattern of consumption is

forecasted to grow as the future estimations predict that in

2020, the energy consumption of the developed economies are

likely to exceed that of the developed countries [1].

The associated negative influences for these consumption

patterns on the ecological systems of the planet impose their

regulation. Hence, the concept of the energy efficient

buildings is an attractive option. The energy efficient

buildings can be characterised by their ability to satisfy both

the proposed design requirements and the operational

demands using the possible minimum energy compared with

other buildings in the same design category [3]. This is mainly

attained via applying the passive environmental design

strategies in addition to utilising the renewable energy

technologies.

In this regard, it may worth mentioning that the thermal

comfort opportunities are defined to a large extent by the

passive design strategies which in turn are mostly defined by

the early design decisions. Thus, it is crucial to analyse and

appreciate the thermal comfort demands in the early stages of

the design in order to satisfy them passively as much as

possible. Under the unavoidable conditions when the HVAC

systems are required to modify the thermal conditions, the

analysis of the thermal demands is still of benefit as it can be

related to control the set points in order to achieve the optimal

efficiency which will be reflected in potential savings.

However, in constructing such buildings, it is crucial to

ensure that the proposed efficiency during the design stages is

reflected in the operational stages as well. In fact, it has been

reported that some of the energy efficient buildings tend to

consume huge amounts of energy in order to keep them

running properly, regardless of the apparent efficiency in the

design stage [3].

The excess consumption of the operational energy may be

partially due to the nature of the method by which the

performance of these buildings is assessed. Frequently, a

simulation approach is implemented to compare the intended

scenario of the energy consumption with an ideal one.

Although the patterns of the occupants' behaviour are often

included, it is difficult to predict the actual patterns.

Therefore, and taking into consideration that most of the

operational energy is consumed to achieve the thermal

comfort, it may be advantageous to view the thermal comfort

demands from the approach of the adaptive models instead of




applying the analytical ones. The former models are

tailored towards specific groups of people in harmony with

certain types of climates and they intensively consider the

behavioural adaptations patterns [4]. As a result, most likely

their predictions will resemble the actual patterns of

consuming the energy in order to achieve the required thermal

comfort.

Additionally and based on the characteristics of the energy

efficient buildings, it can be understood that, at least in certain

periods of the year, these buildings encompass the concept of

the free running buildings that satisfy the heating and cooling

demands passively. In a comparison with the buildings that

depend on the HVAC systems, the free running buildings

reduce the operational energy by around 50% [5]. However, in

the attempt to use less energy, the risk of achieving poor

quality of the indoor environment is obvious. This situation

can partially be avoided by the comprehensive analysis of

both the buildings thermal demands and the site potentials

which leads to defining the periods at which the buildings can

be operated on the free running mode. Inversely, in the

situations of the uncomfortable conditions, the results of this

analysis can be utilized to define adaptive set points that

achieve the maximum potential savings.

II. THERCOM PROGRAMME

Based on the Visual Basic programming language, the

proposed programme (Thermal Comfort in Different Climates

- THERCOM) has been developed to measure and predict the

thermal comfort in the free running buildings (to download a

trial version of the programme, kindly visit:

http://www.nottingham.ac.uk/~lazmbg/MScREA/). It does so

by means of measuring the wet bulb globe temperature index,

the adaptive model for thermal comfort, and the tropical

summer index. In addition, it assess the thermal comfort in the

outdoor environments by means of measuring the wet bulb

globe temperature index, the wind chill index, the discomfort

index, and the heat index.

THERCOM can measure the thermal comfort in

twelve different cities located in three climates based on the

Koppen-Geiger climate classification. Based on the integrated

data, the predictions can be calculated for 24 hours in each

month for all the integrated indices, except those of the

adaptive model for thermal comfort. This exception was due

to the nature of the integrated formula which is based on the

outdoor monthly mean temperature. The integrated climates

are: the equatorial, arid, and warm temperate climates. The

exclusion of the remaining two climates, i.e. snow and polar,

was due to the relatively low populations in regions where

these climates are dominant [6]. More details about the

programme can be obtained from [7].

By predicting the interior thermal conditions, THERCOM

assists in facilitating the selection of the most optimum design

among the different design alternatives through comparing the

thermal performance [5], [8]. In addition, by defining the

periods at which the interior thermal conditions are

comfortable, the programme in fact defines the periods at

which the HVAC system can be switched off in the examined

building. On the other hand, predicting the outdoor thermal

conditions is crucial in order to design the exterior

environments properly as they affect the indoor environments

[9].

III. METHODOLOGY

The concept of the energy efficient buildings implies the

good matching between the site environment and the used

materials and equipment [3]. Based on this, and for the

purpose of the study at hand, four mock-up models were

constructed with different construction materials for the roof.

The thermal performance of these models was investigated

based on the effectiveness of the roof materials in contributing

towards providing the comfortable thermal conditions.

A. Constructional Details

Despite the construction of the roof, the four models share

identical dimensions, properties, and construction materials of

the other parts of the models. They are basically a 3 m x 3 m x

3 m models with one 40 mm foam core plywood door (1 m x

2.2 m) located at the east facade and a single pane of glass

with aluminium frame window (1.5 m x 1.5 m) located at the

west facade. Brick concrete blocks with total thickness of 340

mm were used for the walls and a 100 mm concrete slab

placed on the ground for the floor. The construction of these

elements is detailed in Table 1.

For the roof, the investigated four construction systems

are:

- Cinder concrete with insulation

- Hardboard slab with insulation

- Timber slab without insulation

- Concrete roof with asphalt cover

The detailed components and their properties are displayed

in Table 2.

The models are assumed to be located in Colombo city. It

has been found that the west wind is dominant according to a

previous analysis study of the city climate.

Therefore, the window was positioned on the west facade

in order to encourage the natural ventilation. The wind

velocity was modified based on the wind power low and based

on Melaragno method to account for the changes in the wind

velocity inside the buildings [10].




TABLE 1

CONSTRUCTIONAL DETAILS OF THE MODELS ELEMENTS EXCEPT THE ROOF

Layer Width

(mm)

Density

(kg/m³)

Specific

heat

(J/kg.ºC)

Conductivity

(W/m.ºC)

Wall

Brick

Masonry

Medium

110 2000 836.8 0.711

Concrete

Cinder 220 1600 656.9 0.335

Plaster

Building

(Molded Dry)

10 1250 1088 0.431

Floor

Concrete 100 3800 656.9 0.837

Door

Plywood 3 530 1400 0.140

Polystyrene

Foam 34 46 1130 0.008

Plywood 3 530 1400 0.140

Window

Glass

Standard 6 2300 836 1.046

B. Selected Thermal Index

THERCOM programme was used to compute the thermal

comfort for the explored models by means of calculating the

Tropical Summer Index. This model was selected for the

study at hand based on the coincidence of its climatic

boundaries and the climatic conditions of the chosen city [7].

The investigated period includes 288 hours distributed as 24

hours from each month.

IV. RESULTS AND DISCUSSION

A. Periods of Switching-off HVAC

For each model, the dominant thermal conditions over the

examined period are presented in their percentages of thermal

sensation as depicted in Figure 1. As can be noted from the

pie chart of the first model, a comfortable thermal sensation

was dominant in 83% of the investigated hours followed by

slightly warm sensation with a percentage of 16%. In 1% of

the investigated hours, the dominant sensation was slightly

cool.

For the second model, the pie chart indicates that in 78%

of the examined hours, the thermal conditions were

considered as comfortable. In 21% and 1% of the investigated

hours, slightly warm and slightly cool sensations were

presented respectively. For the third model, the thermal

sensation of 76% of the tested hours was comfortable. In the

remaining hours, a slightly cool sensation was present.

TABLE 2

DETAILS OF THE ROOF CONSTRUCTION

Layer Width

(mm)

Density

(kg/m³)

Specific

heat

(J/kg.ºC)

Conductivit

y (W/m.ºC)

Case 1: Cinder concrete with insulation

Aggregate 10 2240 840 1.8

Rubber natural 2 930 2092 0.138

Polystyrene

foam 50 46 1130 0.008

Polyethylene 1 950 2301 0.502

Concrete cinder 100 1600 656.9 0.335

Plaster ceiling

tiles 10 1120 840 0.38

Case 2: Hardboard slab with insulation

Aggregate 10 2240 920 1.3

Rubber

Polyurethane

elastomer

2 1250 1674 0.293

Hardboard slab 10 1000 1680 0.29

Wool, fibrous 10 96 840 0.043

Board 10 160 1890 0.04

Coat 10 2300 1700 1.2

Case 3: Timber slab without insulation

Sand 10 2240 840 1.74

Rubber 2 1100 2092 0.293

Slab 10 300 960 0.055

Plaster Board 10 1250 1088 0.431

Case 4: Concrete roof with asphalt cover

Asphalt cover 6 900 1966 0.088

Concrete

lightweight 150 950 656.9 0.209

Plaster 10 1250 1088 0.431

The fourth model has a different thermal scenario as

demonstrated from the Figure. The comfortable conditions

were dominant in only 52% of the examined hours, with the

slightly warm and warm sensations forming the remaining

percentages as 42% and 6% respectively.

Based on these percentages, it can be concluded that the

longest period in which the mechanical ventilation systems

can be switched off is of the first model followed by the

second, third, and fourth with percentages of 83%, 78%, 76%,

and 52% respectively.

For the rest of the investigated hours, it may be necessary

to use the HVAC systems to achieve the required comfortable

thermal conditions with an obvious need for cooling in the

four cases.




Fig. 1 Percentages of the thermal sensations of the examined models

A detailed examination of the thermal conditions distributions

as depicted in Figure 2 shows that for the first model, the

mechanical ventilation can be switched off in about 14 hours

from 20 to 10. Although an identical scenario is applicable for

models 2 and 3 as can be noted from the Figure, the scope of

switching off the HVAC systems in the hours from 10 to 20 is

greater for the first model in comparison with the other

models. In the fourth model, the hours at which the HVAC

system can be switched off are limited to around 9 hours in

each of January and February, 6 hours in each of May, June,

November, and December, and the maximum is 13 hours in

each of the months from July to October including both.

Nevertheless, it should not be forgotten that it is possible

to expand the comfortable thermal conditions through the

implementation of the passive design strategies. These

strategies include the proper selection of the materials of the

building envelope, the proper proportion of the openings to

the solid area of the envelope, the orientation, the aspect ratio,

Fig. 2 Hours distribution of thermal sensations of the examined models

Periods of Switching HVAC off




the integration of the shading devices, etc.

Additionally, it should be mentioned that the use of the fans is

permitted [12] as they consume negligible amount of energy

compared with the HVAC systems to achieve an identical

extension of the comfortable conditions.

B. Selecting the Optimum Roof System

From other perspective, the statistical variance of the

tropical summer index temperatures was calculated for the

four models to show values of 1.92, 2.54, 3.11, and 3.89,

where the means of the index temperatures were 28.59 ºC,

28.69 ºC, 28.91 ºC, and 30.29 ºC in sequence.

The narrowest spread of the index temperatures of the first

model from its mean value, in addition to its longest

comfortable period and consequently shortest uncomfortable

periods especially those with slightly warm conditions in

comparison with other models, indicate that the first model

may be considered as the optimum option within the

investigated alternatives.

Table 3 shows the thermal resistance of the four examined

roofs. It is clear from the table that the first model has the best

thermal performance as it has the highest thermal resistance.

A closer look clarifies that this resistance is mainly due to the

presence of the thick insulation layer (layer 3: Polystyrene

foam) which alone contributes of about 95% of the total roof

resistance.

TABLE 3

DETAILS OF THE ROOF CONSTRUCTION

Resistance of Model 1 Model 2 Model 3 Model 4

Layer 1 0.006 0.008 0.006 0.068

Layer 2 0.014 0.007 0.007 0.718

Layer 3 6.250 0.034 0.182 0.023

Layer 4 0.002 0.233 0.023 -

Layer 5 0.299 0.250 - -

Layer 6 0.026 0.008 - -

Total 6.597 0.532 0.218 0.809

Nonetheless, the relatively good thermal performance of

the first model may additionally be partially due to the

combined effect of the high thermal mass of the concrete deck

in addition to the position of the insulation layer where it was

located above the structural deck close to the outer surface.

This according to [11] is the optimum position for the

insulation to insure the most comfortable thermal conditions

in the hot periods. For the first model, the order of the

construction materials with the insulation closer to the outer

surface insures that most of the heat is being prevented from

passing through conduction to the interior layers of the roof.

The permitted amount is absorbed and stored in the thermal

mass of the concrete and thus delayed from affecting the

interior conditions.

Although a fibrous wool thermal insulation was used in

the second model, its thinness and position towards the inner

side of the roof, in addition to the low thermal mass of the

hard board deck, might contributed towards the lower thermal

performance of this model in comparison with the first model.

Moreover, the lack of the insulation layer had an influence

on the much lower thermal performance of the remaining

models. However, the lower thermal mass of the timber slab

of the third model had a relatively positive impact on the

interior thermal conditions as it has a shorter time lag. This

insures that the indoor temperature follows the exterior

temperature. On the other hand, the high thermal mass of the

concrete deck had contributed in the continuous heat stress

during the night period as it can be noted from Figure 2.

IV. CONCLUSION

Under the current rates of energy consumption, it is

important to consider the occupants' behaviour from the early

stages of design as most of the operational energy is

consumed to achieve the thermal comfort. This consideration

is crucial for the energy efficient buildings as the risk of

having poor quality of indoor environment is possible under

the attempts to reduce the consumption of the operational

energy.

Although calculating the thermal resistance may give an

impression about the thermal performance of the examined

roofs, the effect of the different construction systems and

materials on the actual thermal conditions remains unclear.

Hence, it is important to consult tools such as THERCOM to

understand the predicted thermal comfort experience of the

users by means of computing the thermal comfort indices

suitable for the cases under consideration.

THERCOM is of great importance as it helps in better

understanding and good appreciation of the available thermal

comfort opportunities and the deviation from the required

conditions. This understanding helps in making decisions

about selecting the appropriate equipment, materials,

amenities and possibly adjusting the operating patterns which

eventually will increase the efficiency of the buildings.

In the study at hand, four mock-up models were tested to

explore the thermal performance of the roof construction

system and materials. The thermal comfort conditions were

investigated using the tropical summer index. The aim of this

examination was to define the periods at which the HVAC

systems can be switched off and to select the most optimum

construction system among the explored roofs. The first

model, cinder concrete with insulation, had the optimum

thermal performance. Possible factors incorporated to achieve

this performance include the position of the insulation layer,

its high thermal resistance, and the high thermal mass of the

concrete deck.

Furthermore, and in order to extent the comfortable

conditions of the first model further, it is recommended to

select the construction systems of the other parts of the

building envelope based on their thermal properties, in

particular the thermal mass. However, careful planning of the

buildings layouts should be maintained to ensure the

continuity of the natural ventilation.




Finally, it is recommended to perform further

investigations to explore the extent at which the comfortable

thermal conditions may be extended by means of using fans as

a step before the unavoidable use of the HVAC systems.

REFERENCES

[1] L. Yang, H. Yan, and J. C. Lam, “Thermal comfort and

building energy consumption implications - A review,”

Applied Energy, vol. 115, pp. 164-173, 2014.

[2] M. K. Singh, S. Mahapatra, and S. K. Atreya,

“Adaptive thermal comfort model for different climatic

zones of North-East India,” Applied Energy, vol. 88,

pp. 2420-2428, 2011.

[3] A. Meier, T. Olofsson, and R. Lamberts, “What is an

Energy-Efficient Building?,” in Proc. ENTAC, 2002, p.

3.

[4] R. de Dear and G. S. Brager, “The adaptive model of

thermal comfort and energy conservation in the built

environment,” International Journal of Biometeorolgy,

vol. 45, pp. 100-108, 2001.

[5] M. A. Humphreys, H. B. Rijal, and J. F. Nicol,

“Updating the adaptive relation between climate and

comfort indoors; new insights and an extended

database,” Building and Environment, vol. 63, pp. 40-

55, 2013.

[6] A. K. Mishra and M. Ramgopal, “Field studies on

human thermal comfort - An overview,” Building and

Environment, vol. 64, pp. 94-106, 2013.

[7] H. Al-Khatri and M. B. Gadi, “Development of a new

computer model for predicting thermal comfort in

different climates using Visual Basic programming

language,” in Proc. People and Buildings, 2013, paper

MC2013-P24.

[8] N. Djongyang, R. Tchinda, and D. Njomo, “Thermal

comfort: A review paper,” Renewable and Sustainable

Energy Reviews, vol. 14, pp. 2626-2640, 2010.

[9] L. Shashua-Bar, I. X. Tsiros, and M. Hoffman,

“Passive cooling design options to ameliorate thermal

comfort in urban streets of a Mediterranean climate

(Athens) under hot summer conditions,” Building and

Environment, vol. 57, pp. 110-119, 2012.

[10] F. Allard, Natural ventilation in buildings: a design

handbook, Ed., London, UK: James & James, 1998.

[11] I. C. d'Energia, Ed., Sustainable building: Design

manual, New Delhi, India: The Energy and Resources

Institute, 2004, vol. 2.

[12] F. Nicol and M. Humphreys, “Derivation of the

adaptive equations for thermal comfort in free-running

buildings in European standard EN15251,” Building

and Environment, vol. 45, no. 1, pp. 11 - 17, 2012.




Wadi Flow Simulation Using Tank Model

in Muscat, Oman Mohammed Al-Housni

#1, Luminda Gunawardhana

#2, Ghazi Al-Rawas

#3

# Department of Civil and Architectural Engineering, Sultan Qaboos University

P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman

1 [email protected]

2 [email protected]

3 [email protected]

Abstract— In Oman, changes in precipitation intensity and

frequency have already begun to be detected, although the

attributed impacts, such as, flash flooding is poorly understood.

For example, the supper cyclonic storm, hurricane Gonu in 2007

led to the worst natural disaster on record in Oman, with total

rainfall reached 610 mm near the cost. The cyclone and flash

flood caused about $4 billion in damage (2007 USD) and 49

deaths. The objective of this study is to develop a Wadi-flow

simulation model to understand precipitation-river discharge

relationship in Muscat. A lumped-parameter, non-linear,

rainfall-runoff model was used. The Food and Agriculture

Organization (FAO-56) modified Hargreaves equation was used

for estimating reference evapotranspiration (ET0). Precipitation

and temperature data during 1996-2003 were obtained from the

Muscat-airport meteorological station. Observed river

discharges during 26-30, March 1997 were used to calibrate the

model and observations during 1997-2003 were used to verify

our simulations. Simulated water discharges agreed with the

corresponding observations, with the Nash–Sutcliffe model

efficiency coefficient equals to 0.88. This developed model will

later be used with a set of General Circulation Model scenarios

(GCM) to understand the Wadi-flow variations under changing

climate conditions.

I. INTRODUCTION

Oman, located in south-Eastern corner of the Arabian

Peninsula, encompasses a diverse range of topography,

including mountain ranges, low land, coastal areas and arid

deserts. The coastal line of Oman extends over 3165 km and

experiences very severe tropical cyclones. The supper

cyclonic storm, hurricane Gonu in 2007 led to the worst

natural disaster on record in Oman, with total rainfall reached

610 mm near the cost. The cyclone and flash flood caused

about $4 billion in damage (2007 USD) and 49 deaths (Rafy

and Hafez, 2008). Recently changes in intensity and frequency

of the weather events and subsequent impacts demand

countermeasures to adopt with these changes in future.

Hydrological model is an effective tool that could provide

river discharge response attributed to the changes in weather

variables and can be used for planning countermeasures to

cope with the potential impacts.

The tank model developed by Sugawara (1984) is a

lumped parameter, non-linear rainfall- runoff model. The tank

model is composed one, two, three or four tanks laid vertically

in series. Various coefficients represent different hydrological

processes such as surface and subsurface runoff and

infiltration. The different in magnitude of these coefficients in

different catchments reflects the geographical features of the

watersheds. Gunawardhana and Kazama (2012) used the tank

model to study water availability and low-flow analysis of the

Tagliamento River discharge in Italy under changing climate

conditions. Also, this tank model has been used for river

discharge simulations in 12 catchment areas in Japan (Yokoo

et al., 2001). Both studies were done in humid regions, but in

this research, we test the performances of the tank model to

simulate wadi flow in arid region in Oman.

The objective of this study is to develop a Wadi-flow

simulation model to understand precipitation-river discharge

relationship in Muscat (Al-Khoud catchment area). The

developed model is expected to use for climate change

scenarios in future studies to predict wadi flow variations

under changing climate conditions.

II. STUDY AREA

Wadi Al-Khoud in Oman is located in the northern part of

Oman and at the western-north part of Muscat. The

downstream of catchment area is towards northeast Gulf of

Oman (Fig1). The total catchment area approximately is about

1740 km2. The elevation in the catchment area ranges from 41

m at the catchment outlet in Al-Khoud to 2339 m in the inland

mountain area. The climate is arid and it is important for the

water resources, especially for agriculture and domestic

purposes. The annul precipitation occurs in November,

December, March and April as observed from previous data.

The average annual rainfall in Muscat is around 63mm (Al-

Khoud station) to 210 mm (JabalBani Jabir). According to the

meteorological records from 1984 to 2003, the annual average

maximum and minimum temperatures near the catchment

outlet were approximately 33 and 24C°, respectively. The

geology of the catchment area mainly consists of 55% of

igneous and volcanic rocks, whereas, 3% of metamorphic

rocks, 16% of sedimentary rocks and 26% of recent deposits.

III. THEORY

The tank model is a simple non-linear rainfall-runoff

model composed of one or several tanks (Fig. 2). The





coefficients represented for different hydrological

processes (surface and subsurface runoff and infiltration) are

generally obtained by matching observed and simulated data.

Magnitude differences of these coefficients in different

catchments reflect the geographical features of the watersheds.

The rainfall summed to put into the first tank at the top.

Evapotranspiration is directly subtracted from the top tank.

Among the four tanks in the model, first tank at the top

account for rapid runoff near the ground surface and second

tank models the shallow subsurface runoff process. Other two

tanks at the bottom delayed surplus water from the top two

tanks.

Fig. 1. Study area in Oman

This phenomenon represents hydrological role of the deep

aquifers that accumulate the infiltrating water from the ground

surface and released in to the downstream with certain time

delays (Todini, 2007). Representative mathematical model for

the water exchange between tanks and daily runoff generation

can be expressed as follows.

(1)

(2)

(3)

4

1

,

x

nxn RQ (5)

where

x: number of tanks counted from top

n: number of days from the beginning (1/d)

Δt: length of time step

A(x): runoff coefficient of xth

tank (1/d)

B(x): infiltration coefficient of xth

tank (1/d)

H(x,n): water depth in xth

tank at nth

day (mm)

Z(x): height of runoff hole of xth

tank (mm)

R(x,n): runoff from xth

tank at nth

day (mm/d)

I(x,n): infiltration in xth

tank at nth

day (mm/d)

T(n): total input to first tank at nth

day (mm/d)

Evt(n): evapotranspiration at nth

day (mm/d)

Q(n): total runoff at nth

day (mm/d)

P(n): precipitation at nth

day (mm/d)

Fig. 2. Tank model structure for runoff generation

I(x,n) = B(x)× H(x,n)

T(n) = P(n) – Evt(n)

R(x,n) = A(x)× [H(x,n)-Z(x)] H(x,n) > Z(x)

0 H(x,n) ≤ Z(x)

H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[T(n+1)×Δt] x=1

H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[I(x–1, n)×Δt] x≠1

H(x,n+1)=

(4)




TABLE I

TANK MODEL COEFFICIENTS

* based on 12 catchments in southern Japan from Yokoo et al.

The Food and Agriculture Organization (FAO-56)

modified Hargreaves equation, one of the widely used

temperature based method, was used for estimating reference

evapotranspiration (ET0).

aRTTTT

ET

minmax

minmax0 8.17

2

0023.0

(6)

where Tmax(°C) is the maximum daily air temperature,

Tmin(°C) is the minimum daily air temperature, Ra (MJ/m2/d) is

the extra-terrestrial solar radiation and λ is the latent heat of

vaporization (2.45 MJ/m2/d). Actual evapotranspiration was

estimated by matching observed river discharge with

simulations. Precipitation and temperature data during 1996-

2003 were obtained from the Muscat-airport meteorological

station. The Nash–Sutcliffe model efficiency coefficient is

used to assess the predictive power of hydrological models. It

is defined as:

T

t

t

m

t

o

T

t

t

m

t

o

QQ

QQ

E

1

2

1

2

1

where Qo is observed discharge, and Qm is modelled

discharge. Qot is observed discharge at time t. The closer the

model efficiency is to 1, the more accurate the model is. If the

simulated discharges obtained from the tank model and

historical discharges have a trend and significant correlations,

the simulation is considered successful and the tank model can

be used to evaluate the flow phenomena for the concerning

watersheds.

IV. RESULTS AND DISCUSSIONS

Model calibration was done by matching observed river

discharges at gage station at the outlet of the catchment area in

1997 and the model verification was done according to data

observed in 1997, 1999, 2000 and 2003 (Fig.3). Simulated

wadi flow agreed with the corresponding observations, with

Nash-Sutcliffe model efficiency coefficient of 0.88. Table 1

shows the calibrated model parameters in Al-Khoud

catchment area. These model parameters in Al-Khoud were

compared with the derived parameters in 12 catchment areas

in Japan for understanding parameter dependency on different

geographical and climatic settings.

The coefficients of the tank model represent different

hydrological processes of the catchment. As example, larger

A1 coefficient produces higher rapid surface runoff near the

ground surface, while larger B1 coefficient stands for higher

infiltration capacity. According to Table 1, A11 coefficient in

Al-Khoud catchments is smaller than that in Japanese

catchments. This is because top soil layer in Oman catchments

generally has very low soil moisture content due to extreme

dry condition in air and high evaporation throughout the year.

Therefore, infiltration potential is higher and runoff potential

in very shallow subsurface layer is low in catchments in Oman

than them in Japan. For this reason, Al-Khoud catchments

generate smaller A11 coefficients for the tank models than in

Japanese catchments. In contrast, A12 coefficient for Al-

Khoud catchment area is greater than Japanese catchment

area. This can be attributed to the high representative gradient

(RG) of the catchments in Oman than in Japan. Steep slope in

Al-Khoud catchment area increases the runoff potential in the

shallow subsurface layers. Therefore, infiltrated water from

the top soil surface rapidly flows to downstream areas rather

than recharging deep aquifers. For the same reason, Al-Khoud

catchment area has small storage capacities (Z11, Z12 and Z2)

than the Japanese catchments. Moreover the land-use types in

the catchment area have a significant effect in retaining water

in shallow subsurface layers. Absence of full grown trees with

deep spread roots in Oman facilitates rapid subsurface flow

which attenuates groundwater recharge and subsurface

storage. This phenomenon replicate with small Z coefficients

in Oman than in Japan. B1 coefficients between two

catchments also depict significant differences. These

variations indicate that the Al-Khoud catchment has higher

infiltration capacity than the Japanese catchments, which may

also be attributed to the low soil moisture content in Al-Khoud

than in Japanese catchments.

V. CONCLUSIONS AND RECOMMENDATIONS

The objective of this study was to develop a rainfall-runoff

model to simulate Wadi flow in Muscat, Oman. Wadi Al-

Khoud catchment area was selected. Model calibration was

Catchment area Model parameter

A11 A12 B1 A2 B2 A3 B3 A4

Al-Khoud 0.14 0.35 0.37 0.05 0.05 0.02 0.03 0.0003

Southern Japan* 0.4 0.2 0.15 0.1 0.05 0.02 0.03 0.003

Z11 Z12 Z2 Z3 H4 H3 H2 H1

Al-Khoud 1 0.1 5 10 0 0 0 0

Southern Japan* 40 15 20 10 200 40 2 1

(7)

http://en.wikipedia.org/wiki/Hydrology




carried out with observations in 1997. The simulated

Wadi flow model was verified with observation in 1997,

1999, 2000 and 2004. The Nash–Sutcliffe model efficiency

coefficient of 0.88 could be obtained. The calibrated tank

model parameters in Wadi Al-koud catchment area were

compared with the parameters calibrated in several

catchments in Japan. Physical meaning of the tank model

parameters in arid environment could be successfully

interpreted. It was found that the differences of model

parameters of two catchment areas depend on vegetation

cover, topography (RG) and soil moisture content.

The tank model performance highly depends on input data

quality. Lack of long-term quality controlled rainfall and river

discharge records was a major constrain. Respective

authorities are therefore encouraged to maintain a long-term

data base to facilitate academic community.

The results of this study showed the ability of the tank

model to simulate Wadi flow with a reasonable accuracy and

therefore will be applicable for climate impact predictions. In

the next step of this study, downscaled GCMs scenarios from

several models for different climate variables will be used

with the developed tank model to simulate wadi flow

variations in future.

REFERENCES

[1] M. E. Rafy, and Y. Hafez, “Anomalies in meteorological fields over

northern Asia and its impact on Hurricane Gonu,” 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[2] M. Sugawara, “On the analysis of runoff structure about several

Japanese River,” Japanese Journal of Geophysic, vol. 4, pp. 1-76, 1961. [3] L. N. Gunawardhana and S. Kazama, “A water availability and low-

flow analysis of the Tagliamento river discharge in Italy under

changing climate conditions,” Hydrology and Earth System Sciences, vol. 16, pp. 1033-1045, 2012.

[4] Y. Yokoo, S. Kazama, M. Sawamoto and H. Nishimura,

“Regionalization of lumped water balance model parameters based on multiple regression,” Journal of Hydrology, vol. 246, pp. 209-222,

2001.

[5] E. Todini, “Hydrologigal catchment modeling: past, present and future,” Hydrology and Earth System Sciences, vol. 11, pp. 468-482,

2007.




Fig. 3. Observed and simulated wadi flows




Mobile Ad Hoc Networks

Parth Panchal1, Meghana Shroff2 Student, III year, Bachelor of Technology (Electronics)

Mukesh Patel Institute of Technology Management and Engineering NMIMS, SVKM

Mumbai [email protected]

[email protected]

Abstract— A mobile ad hoc network (MANET) is a self-

configuring infrastructure-less network of mobile devices

connected by wireless. The primary challenge in building a

MANET is equipping each device to continuously maintain the

information required to properly route traffic. AODV is a novel

algorithm for the operation of such ad hoc networks. This

routing algorithm is quite suitable for a dynamic self-starting

network, as required by users wishing to utilize ad hoc

networks. AODV provides loop free routes even while repairing

broken links. We attempt to build such a network using AODV.

Keywords— MANET, AODV, Ad hoc, network simulator NS

I. INTRODUCTION

Laptop computers continue to show improvements in

convenience mobility memory capacity and availability of

disk storage. The smaller computers can be equipped with

gigabytes of disk storage high resolution color displays

pointing devices and wireless communications adapters.

Moreover because many of these small (in size only)

computers operate with battery power users are free to

move about at their convenience without being constrained

by wires. More recently the interest in this subject has

grown due to availability of license free wireless

communication devices that users of laptop computers can

use to communicate with each other. Several recent papers

on this topic have focused on the algorithmic complexity of

choosing the optimal set of ad hoc routers while others

have proposed new routing solutions leveraging features

from the existing Internet routing algorithms.

As mentioned earlier, each device in a MANET is free

to move independently in any direction, and will therefore

change its links to other devices frequently. Each must

forward traffic unrelated to its own use, and therefore be a

router. Such networks may operate by themselves or may

be connected to the larger Internet. MANETs are a kind of

Wireless ad hoc network that usually has a routable

networking environment on top of a Link Layer ad hoc

network.

A. Destination-Sequenced Distance-Vector

The Destination-Sequenced Distance-Vector (DSDV)

Routing Algorithm is based on the idea of the classical

Bellman-Ford Routing Algorithm with certain

improvements. Every mobile station maintains a routing

table that lists all available destinations, the number of

hops to reach the destination and the sequence number

assigned by the destination node. The sequence number is

used to distinguish stale routes from new ones and thus

avoid the formation of loops. The stations periodically

transmit their routing tables to their immediate neighbors.

A station also transmits its routing table if a significant

change has occurred in its table from the last update sent.

So, the update is both time-driven and event-driven.

The routing table updates can be sent in two ways: a

“full dump” or an incremental update. A full dump sends

the full routing table to the neighbors and could span many

packets whereas in an incremental update only those entries

from the routing table are sent that has a metric change

since the last update and it must fit in a packet. If there is

space in the incremental update packet then those entries

may be included whose sequence number has changed.

When the network is relatively stable, incremental updates

are sent to avoid extra traffic and full dump are relatively

infrequent. In a fast-changing network, incremental packets

can grow big so full dumps will be more frequent.

B. Dynamic State Routing (DSR)

The key distinguishing feature of DSR is the use of link

state routing. The sender/source knows the complete hop-

by-hop route. The routes are stored in route cache. A route

discovery process is used to dynamically discover routes.

Route discovery works by flooding the network with

RREQ packets. Each node receiving an RREQ rebroadcasts

it, unless it is the destination or it has a route to the

destination in its route cache. Such a node replies to the

RREQ with a route reply (RREP) packet that is routed back

to the original source. RREQ and RREP packets are also

source routed. The RREQ builds up the path traversed

across the network. The RREP routes itself back to the

source by traversing this path backward. The route carried

back by the RREP packet is cached at the source for future

use. If any link on a source route is broken, the source node

is notified using a route error (RERR) packet. The source

removes any route using this link from its cache. A new

route discovery process must be initiated by the source if

this route is still needed. DSR makes very aggressive use of

source routing and route caching.

C. Ad hoc On-Demand Distance Vector (AODV)

AODV discovers routes on an as needed basis via a

similar route discovery process. However, AODV adopts a

very different mechanism to maintain routing information.

It uses traditional routing tables, one entry per destination.

It builds routes between nodes only when it is required by




source nodes and also it maintains these routes as

long as they are needed by these sources. AODV forms

trees which connect multicast group members. The trees

are composed of the group members and the nodes needed

to connect the members. AODV uses sequence numbers to

ensure the freshness of routes. It is loop-free, self-starting,

and scales to large numbers of mobile nodes.

Although AODV does not depend specifically on

particular aspects of the physical medium across which

packets are disseminated, its development has been largely

motivated by limited range broadcast media, such as those

utilized by infrared or radio frequency wireless

communications adapters. We do not make any attempt to

use specific characteristics of the physical medium in our

algorithm nor to handle the problems posed by

channelization needs of radio frequency transmitters.

Nodes that need to operate over multiple channels are

presumed to be able to do so. The algorithm works on

wired media as well as wireless media as long as links

along which packets may be transmitted are available. The

only requirement placed on the broadcast medium is that

neighboring nodes can detect each other’s broadcasts.

AODV uses symmetric links between neighboring nodes. It

does not attempt to follow paths between nodes when one

of the nodes cannot hear the other one however we may

include the use of such links in future enhancements.

II. AODV PROTOCOL

AODV builds routes using a route request (RREQ) and

route reply (RREP) message cycle. When a source node

desires a route to a destination for which it does not

already have a route, it broadcasts a RREQ packet to the

network. Nodes receiving this packet update their

information for the source node and set up backward

pointers to the source node in the routing tables. In

addition to the source node's IP address, current sequence

number, and broadcast ID, the RREQ also contains the

most recent sequence number for the destination of which

the source node is aware.

Fig 1: Route discovery

Fig 2: RREQ Packet Format

A node receiving the RREQ may send a RREP if it is

either the destination or if it has a route to the destination

with corresponding sequence number greater than or equal

to that contained in the RREQ. If this is the case, it unicasts

a RREP back to the source. Otherwise, it rebroadcasts the

RREQ. Nodes keep track of the RREQ's source IP address

and broadcast ID. If they receive a RREQ which they have

already processed, they discard the RREQ and do not

forward it.

Fig 3: Route reply

Figure 4: RREP Packet Format

As the RREP propagates back to the source, nodes set up

forward pointers to the destination. Once the source node

receives the RREP, it may begin to forward data packets to

the destination. If the source later receives a RREP

containing a greater sequence number or contains the same

sequence number with a smaller hop count, it may update

its routing information for that destination and begin using

the better route.

Fig 5: AODV Algorithm

As long as the route remains active, it will continue to be

maintained. Once the source stops sending data packets, the

links will time out and eventually be deleted from the

intermediate node routing tables. If a link break occurs while

the route is active, the node upstream of the break

propagates a route error (RERR) message to the source node

to inform it. After receiving the RERR, if the source node

still desires the route, it can restart route discovery.




The algorithm’s primary objectives are:

• To broadcast discovery packets only when necessary

• To distinguish between local connectivity management

neighborhood detection and general topology

maintenance

• To disseminate information about changes in local

connectivity to those neighboring mobile nodes that are

likely to need the information

Multicast routes are set up in a similar manner. A node

wishing to join a multicast group broadcasts a RREQ with

the destination IP address set to that of the multicast group

and with the 'J'(join) flag set to indicate that it would like

to join the group. Any node receiving this RREQ that is a

member of the multicast tree that has a fresh enough

sequence number for the multicast group may send a

RREP. As the RREPs propagate back to the source, the

nodes forwarding the message set up pointers in their

multicast route tables. As the source node receives the

RREPs, it keeps track of the route with the freshest

sequence number, and beyond that the smallest hop count

to the next multicast group member. After the specified

period, the source node will unicast a Multicast Activation

(MACT) message to its selected next hop. This message

serves the purpose of activating the route. A node that does

not receive this message that had set up a multicast route

pointer will timeout and delete the pointer. If the node

receiving the MACT was not already a part of the multicast

tree, it will also have been keeping track of the best route

from the RREPs it received. Hence it must also unicast a

MACT to its next hop, and so on until a node that was

previously a member of the multicast tree is reached.

AODV maintains routes for as long as the route is

active. This includes maintaining a multicast tree for the

life of the multicast group. Because the network nodes are

mobile, it is likely that many link breakages along a route

will occur during the lifetime of that route. The only other

circumstance in which a node may change the destination

sequence number in one of its route table entries is in

response to a lost or expired link to the next hop towards

that destination.

Once the next hop becomes unreachable, the node

upstream of the break propagates an unsolicited RREP with

a fresh sequence number i.e. a sequence number that is one

greater than the previously known sequence number, and

hop count of ∞ to all active upstream neighbors. Those

nodes subsequently relay that message to their active

neighbors and so on. This process continues until all active

source nodes are notified. It terminates because AODV

maintains only loop free routes and there are only a finite

number of nodes in the ad hoc network. Consider node A

wants to connect to node B, but the link is broken in

between. This means that node A knows that the link to

node B is down and increments the Sequence number and

broadcast it.

III. SIMULATION IN NS2

We have simulated AODV using an event simulator

NS2. The main objective of our simulations is to show that

on demand route establishment with AODV is both quick

and accurate. Additional objectives include showing that

AODV scales well to large networks and determining the

optimal value for each of the necessary parameters.

A. Simulation environment

The simulation experiment is carried out in LINUX

(Ubuntu 12.04). The detailed simulation model is based on

network simulator-2 (ver-2.36), is used in the evaluation.

The NS instructions can be used to define the topology

structure of the network and the motion mode of the nodes,

to configure the service source and the receiver, to create

the statistical data track file and so on.

The following simulation results were obtained

Figure 6: Simulation scenario in the beginning

Figure 7: Simulation scenario




Figure 8: Simulation scenario 2



B. Performance Analysis

For AODV, packet delivery ratio is independent of

offered traffic load, delivering between 85% and 100% of

the packets in all cases. The lazy approach used by AODV

to build the routing information as and when it is created

makes it more adaptive and results in better performance

(high packet delivery fraction and lower average end-to-

end packet delays). In the presence of high mobility, link

failures can happen very frequently. Link failures trigger

new route discoveries in AODV since it has at most one

route per destination in its routing table. Thus, the

frequency of route discoveries in AODV is directly

proportional to the number of route breaks.



Performance of AODV protocols in MANET can be

realized by quantitative study of values of different metrics

used to measure performance of routing protocols which

are as follows:

1) Average End-to-End Delay: It is defined as average

time taken by data packets to propagate from source to

destination across a MANET. This includes all possible

delays caused by buffering during routing discovery

latency, queuing at the interface queue, and retransmission

delays at the MAC, propagation and transfer times. The

lower value of end to end delay means better performance

of the protocol.

End to end delay = Σ (arrive time - send time)

2) Packet Delivery Ratio: It is a ratio of the number of

packets received by the destination to the number of

packets sent by the source. This illustrates the level of

delivered data to the destination. The greater value of

packet delivery ratio means better performance of the

protocol.

PDR = Σ No. of packet received / Σ No. of packet sent




3) Packet Loss: It is the measure of number of packets

dropped by nodes due to various reasons. The lower value

of the packet lost, the better performance of the protocol.

Packet lost = No of packet sent – No of packets received.

III. CONCLUSION

In summary, we present a distance vector algorithm that

is suitable for use with ad hoc networks. AODV has the

following features:

• Nodes store only the routes that are needed

• Need for broadcast is minimized

• Reduces memory requirements and needless duplications

• Quick response to link breakage in active routes

• Loop free routes maintained by use of destination

• Sequence numbers scalable to large populations of nodes

Compared to DSDV and other algorithms which store

continuously updated routes to all destinations in the ad

hoc network our algorithm has longer latency for route

establishment. But within the limits imposed by worst case

route establishment latency, AODV is a sensible choice for

ad hoc network establishment. We look forward to further

development of the protocol for quality of service

intermediate route rebuilding and various interconnection

topologies with fixed networks and the Internet.

A. Future Scope

We believe strongly in the scope of MANET, essentially

in the form of Vehicular Ad hoc Network. Vehicular ad

hoc network is a special form of MANET which is a

vehicle to vehicle & vehicle to roadside wireless

communication network. It has great scope in vehicle

collision warning, security distance warning, driver

assistance, cooperative driving, and cooperative cruise

control, dissemination of road information, internet access,

map location, automatic parking and driverless vehicles. It

also has applications for emergency services, conferencing

battlefield communications and community based

networking.

ACKNOWLEDGMENT

We would like to express our sincere gratitude towards

Mr. Sharad Wagh, Assisstant Professor, NMIMS, for his

technical guidance and constant encouragement throughout

the project, and for his priceless inputs and patience to deal

with our queries.

We would also like to thank the authority of SVKM’s

NMIMS for providing us with a good environment and

facilities to complete this project. Without help of the

aforementioned, we would have faced many difficulties

while doing this project.

REFERENCES [1] C. Perkins, E. Belding-Royer, and S. Das. Ad hoc On- Demand

Distance Vector (AODV) Routing. RFC 3561 (Experimental), July

2003. [2] Y. C. Hu, D. Johnson, and A. Perrig. -SEAD: Secure efficient

distance vector routing for mobile wireless ad hoc networks,‖ in

Fourth IEEE Workshop on Mobile Computing Systems and Applications (WMCSA '02), 2002, p. 313.

[3] Ashokan, Manel Guerrero Zapata. -Securing ad hoc routing

protocols, 2002, ‖ in ACM workshop on Wireless security [4] S. Kent, C. Lynn, J. Mikkelson, and K. Seo. Secure border gateway

protocol (S-BGP) -real world performance and deployment issues,

2000. [5] A. Nagaraju, Dr S Ramachandram and Dr C. R. Rao. Applying

heuristic technique to ad-hoc on demand distance vector routing to

reduce broadcast, ‖ in the World Congress on Engineering Vol II, WCE 2007, London, U.K, 2007

[6] NS-2, The ns Manual (formally known as NS Documentation)

available at http: //www. isi.edu/nsnam/ ns/doc.




Constraints Faced by Rural Women Members in

Functioning of SHGs in Allahabad District

of Uttar Pradesh Rukhsana*, Dipak Kumar Bose**, Priyanka Singh***

*Ph. D. Scholar, **Associate Professor

Departmentt of Agriculture Extension & Communication, Allahabad School of Agriculture SHIATS, Allahabad

***Assistant Professor, Department of Arts for Women

Chitamber School of Humanities Social Sciences, SHIATS, Allahabad

Abstract— The present study was undertaken to study the

constraints faced by rural women members in functioning of

Self Help Groups. Hundred and fifty rural women members of

SHGs from Allahabad district represented the sample for the

study. A structured interview schedule was used for the

collection of data. The findings revealed that the major

constraints faced by the women members were lack of formal

education, no freedom to take decisions, dominance of group

leaders, decision made at administrative level, less cooperation

of officials , less profit, travel expenses for disbursement of loan,

poor monitoring and technical guidance, inadequate space for

enterprise, high cost of raw materials, lack of storage facilities,

non-cooperation between educated and uneducated people and

non cooperation from family members. These constraints may

be solved through extension strategies like adult education,

vocational training of members, facilitating of bank officials and

providing proper marketing facilities.

I. INTRODUCTION

The SHG is a viable organized set up to disburse micro-

credit to the rural women for the purpose of making them

enterprising and encouraging to enter into entrepreneurial

activities. The formation of SHG is not ultimately a micro

credit project but an empowering process. These SHG have

common perception of need and an impulse towards

collective action. Empowering women is not just for

meeting their economic needs but also for more holistic

social development. The SHGs empower women both

socially and economically. They encourage women to

participate in decision making in the households,

community and local democratic sector and prepare women

to take up leadership position. (Ramachandran and

Balakrishnan 2008).

The SHG-Bank linkage model is the indigenous model

of micro-credit evolved in India and has been widely

acclaimed as a successful model. SHG-Bank linkage

programme is considered a promising approach to reach

the poor and has since its inception made rapid strides

exhibiting considerable democratic functioning and group

dynamism. The number of 500 Bank linked SHGs in 1991-

1992 has gone up to more than 34 lakh by the end of

March 2008. Cumulatively, these SHGs have accessed

credit of Rs. 22,268 crore from banks during the period.

About 4.1 crore poor households have gained access to the

formal banking system through the programme. The faster

growth in bank loans to SHGs has led to almost a four-fold

increase in the average loans per SHG from Rs. 16,816 in

1999-2000 to Rs. 63,926 in 2007-08. These figures reflect

the outstanding success of the programme. (Kumar and

Golait, 2009).

On the other hand it has been revealed through various

research studies that the real economic growth of the SHG

beneficiaries has not been achieved. Despite policy

initiatives, the extent of inclusion is very low in rural and

semi - urban India. There are still 90 million people who

are excluded from the formal banking system for various

reasons like lack of knowledge in the rural poor related to

banking and banking products, high transaction costs and

illiteracy. In this scenario, microfinance, which is defined

as the provision of financial services to the low income and

vulnerable groups of the society is playing a challenging

role in achieving twin goals of financial inclusion and

poverty eradication in economically viable manner. (Rupa

et al 2012)

Mehta (2012) also reported some major issues and

problems indicating SHG status. Most members of the

SHG have no knowledge about the SHG and they do not

have a principal occupation. Women member perform dual

role in society relating to production and reproduction so

they are over burdened and their contribution to the family

economy and national economy remains largely invisible

and undervalued. The existing communication channels are

not adequate and do not reach to the BPL members of the

society. There is unchecked exploitation of SHG women

members in houses, at working place and public place.

Despite all the notable efforts on part of the government

and non- government agencies, access to financial services

for all at affordable rates remains a distant dream.

Remoteness of rural areas and poor infrastructure leads to

market inefficiencies and a huge gap between demand and

supply. Problem is compounded by the fact that rural

population is still largely illiterate and not so technology

driven. Kumar and Anand (2007). Critical gaps have been

observed in the management of day to day activities of the




Self Help Groups relating to different group

dynamics, organizational management, financial

management, arrangement of livelihood activities, internal

monitoring, accountability etc. Intensive and extensive

training programmes involving community resource

persons, coordinators will have to be organized for existing

as well as new Self-help Groups, so that village level

organizations (Primary Federations) can be conveniently

formed with the help of these groups. (Zakir et al 2011).

II. MATERIALS AND METHODS

The present research study was conducted in three

blocks of Allahabad District of UP viz; Chaka, Jasra and

Handia. A list of SHGs operating in these three blocks was

obtained from the block office. A proportionate random

sample of 30 Self Help Group was selected from the three

selected blocks. Five office bearers (women members)

from each selected Self Help Group was taken as the

sample of the study, thus a total of 150 respondents were

selected for the present study. An interview schedule was

constructed which consisted of list of statements related to

personal constraints, organizational constraints,

economic/financial constraints, managerial constraints,

social constraints and marketing related constraints. The

data was collected through personal interview method by

using pretested structured interview schedule and the

collected data were compiled, tabulated and analyzed.

III. RESULTS AND DISCUSSION

After analyzing the data regarding socio-economic

characteristics it was found that majority of the

respondents were in the age group of 30-40 years

(50.66%), married (85.33%), illiterate (48.67%), had

nuclear family (62.67%) and were daily wage labours

(48.67%).

A. Personal problems faced by the respondents

The data with regard to personal problems faced by the

respondents are presented in table 1. It is evident from the

table that majority of the respondents i.e. 68.67 per cent

faced the problem of lack of formal education and got

ranked I. TABLE I

DISTRIBUTION OF RESPONDENTS ACCORDING TO THE PERSONAL PROBLEMS FACED

N=150

Personal problems Frequency Percentage Rank

No freedom to take

decisions

42 28.00 II

Lack of motivation 26 17.33 III

Lack of formal

education

103 68.67 I

*multiple response

Most of the SHGs members were illiterate, due to which

they lack confidence and are unable to take decision at

their own. In the study it was found that about 28 percent

of the respondents had no freedom to take decisions (II

Rank) and 17.33 per cent of the respondents were those

were having the problem of lack of motivation and placed

at III rank.

B. Organisational Constraints Faced by the Respondents

The table 2 reveals the data regarding the organisational

constraints faced by the SHG members which clearly

indicates that about half of the respondents reported that

the decision related to group functioning and income

generating activities were taken at higher level and the

respondents were not involved into it. Near about 28.67 per

cent of the respondent complain of conflicts among group

members resulting in non cooperation among the group

members. TABLE II

DISTRIBUTION OF RESPONDENTS ACCORDING TO THE

ORGANIZATIONAL CONTRAINTS FACED N=150

Organizational

constraints

Frequency Percentage Rank

Dominance of group

leaders

88 58.67 I

Conflicts in group 43 28.67 V

Lack of participatory

approach

59 39.33 III

Irregular meetings 21 14.00 VII

Decision made at

administrative level

74 49.33 II

Poor record keeping 37 24.00 VI

Inadequate training 44 29.33 IV

*multiple response

The constraints of dominance of group leaders was

reported by about 58.67 per cent of the respondents (Rank

I) while 39.33 per cent were those who faced the problem

of lack of participatory approach. The problem of irregular

meeting was reported by about 14.00 per cent of the

respondents (rank VII) followed by 24.00 per cent who

complain that the records were not maintained properly

(rank VI) and about 29.33 per cent complaint of inadequate

training.

C. Economic/Financial constraints faced by the

respondents

The table 3 indicates the economic/financial constraints

faced by the SHG members. It is revealed from the table

that a large percentage of the respondents i.e. 62.67 per

cent felt that the profit earned through the income

generating activities are too little (rank I) followed by

54.67 per cent who reported that it was an extra burden for

them to arrange for travel expenses to visit the bank often.




TABLE III

DISTRIBUTION OF RESPONDENTS ACCORDING TO THE ECONOMIC/ FINANCIAL CONSTRAINTS FACED

N=150

Economic/ Financial

constraints


Inadequate loan

transactions

32 21.33 IV

Exhaustive procedure in

getting loan

28 18.67 VI

Travel expenses for

disbursement of loan

82 54.67 II

Irregular saving

procedure and loan

repayment of members

49 32.67 III

Less cooperation of

officials

30 20.00 V

Less profit 94 62.67 I

Short duration of

repayment of loan

17 11.33 VII

*multiple response

About 21.33 per cent of the respondents reported that the

loan amount disbursed to them is insufficient to start a

profitable venture and got IV rank. The constraints at the

III rank was reported by about 32.67 per cent of the

respondents who complaint of irregular saving procedure

of the members and some of the members of SHGs did not

repay loan amount in time. About 18.67 per cent of the

respondents faced the difficulties in disbursement of loan

due to exhaustive procedure (VI rank) followed by 11.33

per cent who felt that the duration of repayment of loan is

short and must be increased and this constraints was placed

at VII rank.

D. Managerial constraints in functioning of SHGs

The data enfolded in table 4 shows the managerial

constraints faced by the respondents. It is clear from the

table that about 45.33 per cent of the respondents faced the

difficulties of poor monitoring and technical guidance (I

rank) and about 28.67 per cent of the respondents had the

constraints of lack of space for the enterprise which was

ranked II. TABLE IV

DISTRIBUTION OF RESPONDENTS ACCORDING TO MANAGERIAL CONSTRAINTS FACED

N=150

Managerial constraints Frequency Percentage Rank

No exposure in record

maintenance

38 25.33 III

Inadequate space for

enterprise

43 28.67 II

No permanency in

getting materials

32 21.33 IV

Unskilled women group

members

10 6.67 V

Poor monitoring and

technical guidance

68 45.33 I

*multiple response

About 6.67 per cent of the respondents had unskilled

women group members in their SHG followed by 25.33 per

cent who complaint of no exposure in record maintenance

and were placed at V and III rank respectively. No

permanency in getting the material was faced by about

21.33 per cent of the respondents and got IV rank.

E. Marketing Constraints Faced by the Respondents

There were some marketing related

constraints faced by the respondents which are presented in

table 5. About 36 per cent of the respondents faced the

problem of high market cost of raw material which got I

rank. The raw material for the dairy, piggery and goat

rearing is fodder and the medicines when their animals fell

ill. The market cost of veterinary drugs was perceived as

high by the respondents. SHG members engaged in

namkeen making felt the market cost of besan, peanut etc

was high. TABLE V

DISTRIBUTION OF RESPONDENTS ACCORDING TO THE MARKETING RELATED CONSTRAINTS FACED

N=150

Marketing related

constraints


No market demand of

the product

32 21.33 II

Lack of transportation 17 11.33 V

Lack of storage

facilities

22 14.67 IV

Lack of market

information

30 20.00 III

High cost of raw

materials

54 36.00 I

*multiple response

Lack of market demand of the product was faced by

about 21.33 per cent of the SHG members (II rank)

followed by 20.00 per cent who lack the information of

market demand and placed at III rank. Near about 14.67

per cent of the respondents had no storage facilities due to

lack of space while, problem of lack of transportation was

faced by about 11.33 per cent of the SHG members and

these problems got IV and V rank respectively.

F. Social Constraints Faced by the Respondents

The data set in table 6 shows the social

problems faced by the respondents. The data clearly

indicates that the problem getting rank I was faced by

about 25.33 per cent of the SHG members who reported the

problem of conflict among educated and uneducated people

due to differences in cognitive understanding. About 22.67

per cent of the respondents faced the problem of

jealousness of friends and neighbor (rank II) while only

about 7.33 per cent of the SHG members were those who

faced the problem of caste system in the group/village.




Table 6: Distribution of respondents according to the

social constraints faced by them (N=150)

Social constraints Frequency Percentage Rank

Non cooperation from

family members

17 11.33 IV

Jealousness of friends

and neighbor

34 22.67 II

Cultural taboos not

permitting

29 19.33 III

Non-cooperation

between educated and

uneducated people

38 25.33 I

*multiple response

About 11.33 per cent of the respondents faced the

problem of non cooperation of family members followed

by 19.33 per cent who faced the difficulty of cultural

taboos.

IV. CONCLUSION

The study therefore reflects that the major constraints

faced were lack of formal education, no freedom to take

decisions, dominance of group leaders, decision made at

administrative level, less cooperation of officials, less

profit, travel expenses for disbursement of loan, poor

monitoring and technical guidance, inadequate space for

enterprise, high cost of raw materials, lack of storage

facilities, non-cooperation between educated and

uneducated people and non cooperation from family

members. These constraints may be solved through

extension strategies like adult education, vocational

training of members, facilitating of bank officials and

providing proper marketing facilities.It is therefore

suggested that the women members need to be sufficiently

exposed to the objectives and functioning of the SHGs so

that they could manage the group effectively. This also will

develop their interest in undertaking various activities with

credit facilities, need based training and generate income

which will definitely make them empowered.

REFERENCES

[1] T. Ramachandran and S. Balakrishnan, Impact of Self

Help Groups on Women’s Empowerment- A Study in

Kanyakumari District. Kurukshetra vol. 57(2), pp. 1-

34, 2008.

[2] P. Kumar and R. Golait, Bank Penetration and SHG-

Bank Linkage Programme: A Critique Reserve Bank

of India Occasional Papers, vol. 29(3), pp. 119-138,

2009.

[3] J.S. Rupa, M. Majumdar, V. Ramanujam, Self Help

Group (SHG) - Bank Linkage Model– A Viable Tool

for Financial Inclusion. Journal of Economics and

Sustainable Development vol. 3(10), pp. 134-142,

2012.

[4] M.C. Mehta, Self Help Groups – Its Rural

Impediments. International Journal of Scientific and

Research Publications, vol. 2(5), pp.1-3, 2012.

[5] S. Kumar and S. Anand, Journey of Rural Credit in

India over the Past Sixty Years, Kurukshetra vol.

55(12), pp. 52-54, 2007.

[6] A.M.M. Zakir, N. Baruah, K. Kalita, Management of

Self Help Groups, http://sirdassam.in/PDF/

SGSY/Publish_Books/Management_of_Self_Help_Gr

oups.pdf, 2011.

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