education for chemical engineers 4 ( 2 0 0 9 ) e9–e19
Contents lists available at ScienceDirect
Education for Chemical Engineers
journa l homepage: www.e lsev ier .com/ locate /ece
ABVIRTUAL—A virtual platform to teach chemicalrocesses
.G. Rasteiroa,∗, L. Ferreiraa, J. Teixeirac, F.P. Bernardoa, M.G. Carvalhoa, A. Ferreiraa,.Q. Ferreiraa, F. Garciaa, C.M.S.G. Baptistaa, N. Oliveiraa, M. Quinaa, L. Santosa,.A. Saraivaa, A. Mendesb, F. Magalhãesb, A.S. Almeidab, J. Granjoa, M. Ascensoa,.M. Bastosa, R. Borgesa
University of Coimbra, Faculty of Science & Technology, Chemical Engineering Dep., Rua Sílvio Lima, 3030-790 Coimbra, PortugalUniversity of Porto, Faculty of Engineering, PortugalUniversity of Coimbra, Faculty of Science & Technology, Mathematics Dep., and Telecom. Inst., Portugal
a b s t r a c t
The need to develop the capacity for autonomous and critical thinking in students and introduce practical approaches
that complement the scientific background, have been acting as driving-forces that motivate engineering educators
to develop new teaching methodologies. The Chemical Engineering Departments of both the Universities of Coimbra
and Porto have been experimenting in this area and addressing these concerns. Recently, they have been engaged
in a broader project, involving a large group of academics with complementary competencies. This project is aimed
at developing a virtual platform directed towards the learning of Chemical Processes with a wide scope. From the
functional point of view the platform is organized into four main areas: Chemical Engineering, Chemical Processes,
Virtual Experiments and Simulators. The Chemical Processes area is further divided into four different sections:
Unit Operations and Separations, Chemical Reaction, Process Systems Engineering and Biological Processes. These
sections include simulators, applications and case studies to better understand the chemical/biochemical processes.
The Virtual Experiments area considers both the laboratory visualization of the basic phenomena related to the
processes in the other four sections, and the remote monitoring of laboratory experiments. This platform, constructed
around a dynamic Web Portal, allows discussion forums and is also aimed at sharing experiences with other schools.
This paper describes the different subjects included in the web platform, as well as the simulation strategies and the
web methodologies used for its construction, and also presents examples of application in the classroom.
Keywords: Chemical processes; E-learning; Virtual laboratories; Computational platform
of Clark K. Colton from the Massachusetts Institute of
. Introduction
eaching methodologies have been changing all overhe world, including in Engineering Education. Educatorsant their students to develop analytic capabilities and
utonomous and critical thinking. However, they face, quiteften, difficulties resulting from the strategies adopted athe basic education level, and also from the diversity ofackgrounds that students have when they enroll in a uni-
ersity degree course. In addition, engineering students needo develop a practical approach to the subjects addressed, in
∗ Corresponding author.E-mail address: [email protected] (M.G. Rasteiro).Received 29 June 2008; Received in revised form 19 January 2009; Acce
parallel to the scientific background. These facts have beenacting as driving-forces to motivate engineering educators todevelop new teaching methodologies.
Online Internet laboratories have been under develop-ment since the 1990s: see, for instance, Henry’s referencesfrom the University of Tennessee, Chattanooga, USA (http://chem.engr.utc.edu/jim-henry/jmh-references.htm; http://chem.engr.utc.edu/) or the work of Jesus del Álamo and
pted 18 February 2009
Technology, USA (http://groups.csail.mit.edu/mac/projects/icampus/projects/ilab.html) together with those of R. Moros
neers. Published by Elsevier B.V. All rights reserved.
(http://como.cheng.cam.ac.uk/proj.wbt.html) and MarkusKraft, both from the University of Cambridge, UK (http://www.cambridge-mit.org/project, as a result of the Cambridge-MIT partnership programme). A review paper presentedby Kadiyala and Crynes (2000) provides an overview ofthe effectiveness of information technologies in educa-tion. In fact, these tools facilitate the development ofadditional teaching strategies for simulation, demonstra-tion, experimentation, operation, and so on, contributingto engaging students and to developing a truly activelearning attitude (Felder, 2006). Therefore, using dif-ferent resources, the dynamics in the classes couldincrease.
However, many of the virtual laboratories and simulatorsdeveloped so far are quite limited in the sense that each ofthem only deals with specific subjects, for instance, trans-port phenomena, unit operations or control (Selmer et al.,2007; Vaidyanath et al., 2007; Edgar, 2006; Klein and Wozny,2006; Henry and Schaedel, 2005; Streicher et al., 2005). On theother hand, this portal focuses on a wide range of subjectsand brings together contents (like e-books), simulators, virtualexperiments and remote control experiments. The integrationof Chemical Engineering subjects is our uppermost objective,but other learning outcomes can be achieved with this multi-purpose portal:
- In more realistic problems (open-ended and multidis-ciplinary), simulators help obtain solutions within areasonable timescale in class or at home, and train criti-cal and creative thinking while also preparing students tooptimize process designs.
- The underlying philosophy of the portal is against using thesimulators as black boxes; in mini-projects, students canimprove existing programs, which can then be introducedback into the platform with two purposes: developing com-puter programming skills, recognizing the assumptions tobe made, associated errors, input/output relationships andenhancing structured thinking.
- Virtual labs complement Real labs: the latter give students“hands-on” exposure, where they can feel the equipmentand how it operates; the former help prepare the student tobe more productive in the Real laboratory.
- The virtual lab allows students to experience an industrialcontrol room as LabVIEW® computer interfaces are simi-lar in both cases; they can also explore operating scenarios
Fig. 1 – Scheme o
eers 4 ( 2 0 0 9 ) e9–e19
which might not be easily or economically studied with realequipment.
- Remote control experiments prepare students for operatingcomputers in networks of some industries whose processesare increasingly remotely controlled.
The Bologna Process, which aims at creating a Euro-pean Higher Education Area (The Bolonha Declaration, 1999;Molzahn, 2004; EUA Bologna brochure, 2008) having led to thereorganization of the higher education curricula in Europeaccording to a three cycle structure, suggests a reductionof formal lecture hours and stresses the importance ofautonomous work. In Portugal, it was only in the academicyear 2006/2007 that the Bologna Process started to be imple-mented, which has worked as a further motivation for thedevelopment of new teaching methodologies. These havebeen undertaken for quite some time by the Chemical Engi-neering Departments of the Universities of both Coimbra andPorto (Rafael et al., 2007 and Mendes, 2002), on their own,taking into consideration the above-mentioned concerns, andalso taking advantage of the information technology skillsdemonstrated by students. Recently, these departments havebeen engaged in a broader project, involving a large group ofacademics (15 Chemical Engineering Faculty members and 5research students) with complementary competencies. Thisproject is aimed at developing a virtual platform with a widescope, directed towards the learning of Chemical Processes, forPortuguese-speaking students, including those from African,American and Asian countries. The portal home page ishttp://labvirtual.eq.uc.pt.
The portal includes four different areas: Chemical Engi-neering, Chemical Processes, Virtual Experiments and Simu-lators. The Chemical Engineering area addresses the generalpublic, enabling students from the basic education levels toobtain information on what Chemical Engineering is about,Chemical Engineering History, new developments in Chemi-cal Engineering (such as Energy and Environment, Biosystemsand Nanotechnologies), and also new trends in Chemical Engi-neering Education. In a subsection intended for secondaryschool students, we try to make a connection between basicscientific concepts (physics and chemistry) and ChemicalEngineering applications, taking into account the level of
knowledge at that school stage (Rasteiro et al., 2008). TheChemical Processes area comprises four sections: Unit Oper-ations and Separations, Chemical Reaction, Process Systems
ngineering, and Biological Processes, as shown in Fig. 1.hese sections deal with the chemical/biochemical processesnd present fundamental concepts and applications aimed ateading the students to understand, for instance, how differ-nt operating conditions result in different process designs,r which alternatives are available for a certain process, etc.henever possible, process integration is also addressed.oreover, each section includes case studies illustrating some
f the features of the applications developed. The Simula-ors can be accessed directly from each section of Chemicalrocesses although they are assembled in a separate sectionhich includes all the simulators developed (around 20).
The Virtual Experiments section deals both with the lab-ratory visualization of the basic phenomena related to therocesses presented in the other sections, and with the remoteonitoring of laboratory experiments. Additionally, these
isualizations will also be used to help students to better pre-are their lab classes, in order to take the maximum benefitrom them. The modules mentioned above have already beenn use in Chemical Engineering undergraduate classes sincepril 2008.
This site is intended to be a dynamic Web Portal open tohare experiences with other schools and educators. In thisaper we will briefly explain the objectives of the differentodules which make up the virtual platform, with partic-
lar attention given to some of the applications already inse in the classroom. In addition, a brief explanation of theimulation strategies and web methodologies adopted in theevelopment of the portal will be presented. At the end, somexamples of using the platform in the classroom to teachhemical Processes will also be shown, as well as a first assess-ent by the students.
. Construction of the virtual platform
.1. Simulation strategy
ne of the key components of the platform is process sim-lation. The study of the different chemical processes isupported by twenty interactive simulation modules, cover-ng both fundamental topics as well as more practical andomplex applications. Fig. 2 depicts the basic architecture ofhe system, comprising two main blocks: the web interface,hich helps the user enter the data required for simulation
nd supports the visualization of the corresponding results,nd the computational platform, where the mathematical modelf the chemical process is solved. The exchange of informationetween these two levels is mediated by a simulation gateway,esigned in accordance with the CGI (Common Gateway Inter-ace) protocol. The input data set supports numerical valuess well as discrete options (chemicals to be processed, type
f model to be used or different modes of simulation). Theimulation output may include graphics and in some cases
Fig. 2 – Flowchart with the simulation components.
rs 4 ( 2 0 0 9 ) e9–e19 e11
several sets of results for different input conditions and alsodynamic profiles drawn in real time. It should be noted thatthe simulations are entirely run on the server; the user justneeds a regular browser to access and interact with the plat-form. The server is based on the open-source Apache software,freely available on the Internet. The users’ administration isalso carried out using the facilities provided by this software.
Matlab was chosen to implement most of the capabilitiesof the computational platform, although other tools are alsoused such as Octave and FORTRAN, for greater flexibility andfaster execution, or to use previously developed codes. Mat-lab is a well-recognized general-purpose simulation languagecombining numerical and graphical capabilities, providing anextensive library of add-on packages. It is widely used in engi-neering teaching, research and industrial practice, and is partof the chemical engineering curriculum at the partner uni-versities. In addition, it is affordable and easy to integratewith other applications (Chapra, 2005). However, the modularnature of the platform allows the use of different simula-tion languages and systems, through a relatively simple dataexchange interface.
Regarding the mathematical process models embedded inthe simulators, the level of detail, complexity and generalityvaries from application to application. They may correspondto sets of algebraic and/or differential equations, dependingon the process operating mode (continuous or batch) andon the model class (lumped/distributed parameter system).These sets of equations are solved using standard numericalmethods; in more complex problems, decomposition strate-gies and/or iterative procedures may also be needed. Thesetools are in most cases recognizable by the students who arethus prepared to explore the codes, understand details andadapt or extend them for particular homework and projects.
In some modules, a database of physicochemical proper-ties for a limited set of chemicals is available and simulationscan be performed for different feed mixtures. Modularity isalso explored in several cases, with process simulators accom-modating several more fundamental modules. For instance,there is an autonomous module of vapour–liquid equilibriumto perform calculations such as the boiling point of a liquidmixture, which is also invoked within the distillation mod-ule, where large scale equipment to separate a liquid mixtureis simulated. In other cases, the simulation modules are notinterconnected and calculations can only be made for a par-ticular process feed. It should be noted, however, that ourconcern is not to develop a professional platform with largedatabases and a sophisticated interconnection structure, butinstead to build a pedagogical tool. In this regard, the set ofmodules so far developed is of great value, and is intendedto be expanded in the future with other illustrative processesand applications.
Moreover, additional compounds can be easily introducedin the physicochemical properties database. In some modulesthe user can even feed in his own experimental data, either asdiscrete values or as correlations.
2.2. Web methodologies
The web infrastructure of the Virtual Laboratories of Chemi-cal Processes site is based on standard open-source and freely
available software. This approach allows similar functional-ities to existing commercial software, with the flexibility tobetter adapt to the specific needs of this portal.
ngin
e12 education for chemical e
Since one of the portal’s goals is to support initial andlifelong learning processes, the use of a Learning Manage-ment System was one possible natural option. In this case, wedecided to use a Virtual Server that can seamlessly integratecontents from various sources, and present these contents ina consistent way to the user. Most of the materials availableare stored in a Content Management System (CMS), for flex-ibility and to simplify the inclusion of new material. Joomla!,one of the best-known content management systems, is wellsuited to this task. Predefined presentation templates simplifythe addition of new contents, and the management of severalkinds of information such as texts, images, forms, lists, etc.
The integration of simulators and data acquisition systemswith the Web Portal is a critical point, to accommodate sim-ulators developed in different programming languages, andwith LabVIEW® for remote access to real instrumentationequipment. Since the CMS used allows the construction of cus-tomized templates for the presentation of information, thisintegration is made by developing forms to visualize and man-age real time data, and for the insertion of parameters used bythe simulators to run calculations and present the results tothe users. These forms are developed using the Perl program-ming language, through Perl scripts, acting as the SimulationGateway. This layer validates the user input and executes asystem call to autonomous simulation codes. As a result ofa successful simulation, graphical and numerical results canbe returned, to be displayed on the web page as results. Thechoice of Perl for the CGI layer is due to the flexibility pro-vided by this programming language for implementing theforms, validating the data, and connecting to existing simula-tion resources.
In addition to these functionalities, the use of Joomla! allowsthe installation of additional components and modules, tosupport other functionalities of the portal such as discussionforums, search boxes, online surveys, lists of documents avail-able for downloading, etc.
3. The portal topics
The main features of the four different blocks in the Chem-ical Processes area will be presented. Each block, as shownin Fig. 1, includes a library of fundamental concepts, modelsand applications, simulators and case studies to lead the stu-dents through the study of the process concerned. Quite often,there are also links to applications in other web sites. More-over, some processes are simultaneously illustrated throughweb visualizations of laboratory experiments, in the “VirtualExperiments” section, which interacts with all the other mod-ules.
3.1. Unit Operations and Separations
This section is directed to the study of Unit Operations, espe-cially Separation Processes applied to Chemical Processes. Fivedifferent separations, addressing both equilibrium and rate-based processes, have been considered so far: (1) distillation,(2) liquid/liquid extraction, (3) absorption, (4) adsorption andion-exchange and (5) crystallization. In the future, other pro-cesses will be considered, namely involving a disperse phaseand unit operations dealing with heat transfer. It must be
stressed that the processes selected for inclusion in the por-tal are quite typical of Chemical Industries and also equallyimportant for Bioprocesses. In the section of Biological Pro-
eers 4 ( 2 0 0 9 ) e9–e19
cesses other more specific separation processes are alsoaddressed.
Due to their major importance to all processes, Ther-modynamics and Heat and Mass Transfer Fundamentalswere considered as autonomous modules, preceding the UnitOperations and Separations section. In the Thermodynamicmodule both vapour/liquid and liquid/liquid equilibrium areaddressed. The student is guided from the easier (idealgas and ideal liquid) to the more complex approaches (realgas described through Virial coefficients and real liquid,using the UNIFAC method). The module includes severalcase studies, where the calculated results are comparedwith experimental data, so that the student assesses thevalidity of the different models for the specific systems anal-ysed. Moreover, in this section, there are links to other websites using other approaches for vapour/liquid equilibrium,namely, those based on state equations and molecular sim-ulation.
The module on Heat and Mass Transfer Fundamentalsstarts with the description of the three basic mechanisms ofenergy transfer (conduction, convection and thermal radia-tion) and the corresponding fundamental equations for theevaluation of the energy transfer rate. Since most of the heattransfer processes involve more than one of these energytransfer modes, combined mechanisms in series are also con-sidered. A composite wall having layers of different materialssurrounded by fluids at different temperatures is an exampleof such a process. Mass transfer resulting from concentrationdifferences also plays an important role in many industrialprocesses as in the Unit Operations and Separations sectionconsidered in this site. The mechanisms of mass transfer(molecular diffusion and convection) are addressed and thebasic rate equations are applied to mass transfer in gases,liquids and porous solids. The cases of gas absorption and dif-fusion through membranes surrounded by fluids are used toillustrate mass resistances in series and to identify an overallmass transfer coefficient. Many of our day-to-day experiencesinvolve heat and/or mass transfer. Therefore, several exam-ples are presented to illustrate the transport mechanismsassociated with everyday situations.
Referring to the different separation processes, in eachmodule there is always a section on fundamentals, followedby another section describing the models used in the simu-lation and then the design program which can be accessedthrough the platform. Moreover, for each separation process,different case studies have been prepared, which can help thestudents understand different aspects of the process itself,namely the influence of operation conditions on the designand performance of the separation equipment.
For the design of distillation equipment both a short-cutand the rigorous Wang-Henke method (Henley et al., 1981)have been implemented. As for the design of liquid/liquidextraction equipment a McCabe–Thiele type method (Wankat,2007) has been implemented, which is only valid when bothsolvents can be considered immiscible.
Both distillation and extraction pilot columns are avail-able for the Chemical Engineering students at the Universityof Coimbra. Therefore, the students have the opportunity toapply the theory and the models available in the platform totreat and understand the experimental data they obtain in thelaboratory. In the future we intend to integrate demonstra-
tions of both distillation and extraction experiments into thevirtual experiments area of the platform, as we have now forother processes.
inee
MiseKuKtei
gi
upatflaucftlGTp
erptpiuTaMrmttiittpsnspr
mikr
tto
education for chemical eng
The design of tray absorption towers is based on thecCabe-Thiele method for the determination of the theoret-
cal number of trays. Stripping is covered as well in a secondimulator. When the user introduces a linear equilibriumquation, the number of trays is also determined using theremser equation (valid, in general, for diluted solutions). Theser can then compare the results and verify the validity of theremser equation assumptions. Case studies exemplifying
he use of both simulators are presented, where the influ-nce of different operating conditions on design parameterss illustrated.
The rate-based processes considered in the platform areas/liquid absorption in packed towers and adsorption andon-exchange in solid/liquid systems.
With the simulator “Absorption in packed columns” theser can choose between calculating one or all the designarameters: packing height, column diameter, pressure-dropnd flooding mass flux. Two approaches are used to calculatehe height of packing: (i) the product of HTU (Height of Trans-er Unit) and NTU (Number of Transfer Unit) both based oniquid or gas phases, and (ii) the result of the mass balances todifferential volume for the counter-current flow pattern. Theser also has to introduce the values or choose the empiricalorrelations used to estimate either individual mass trans-er coefficients or HTU. The case studies exemplify severalypes of calculations that can be performed with the simu-ator, using empirical correlations given by Wankat (2007) andeankoplis (2003) for pressure-drop and HTU, respectively.he influence of different operating conditions on the designarameters is also illustrated.
For the design and optimization of the adsorption and ion-xchange processes knowledge of equilibrium and kinetics isequired. The simulator “Adsorption” consists of two majorarts. In the first part the user gets information on the par-ition equilibrium between the liquid and solid (adsorbent)hases based only on pure component isotherms. After insert-
ng the experimental data, the data set can be correlatedsing four different isotherm models: Langmuir, Freundlich,óth, and Nitta. The isotherm parameters are obtained byleast squares minimization using an algorithm from theatlab optimization toolbox. The second part contains algo-
ithms for carrying out kinetic studies. The user can chooseodels for studying the kinetic behaviour of batch, CSTR (con-
inuous stirred tank) and fixed-bed adsorbers; it is possibleo obtain the temporal evolution of the solute concentrationn the external solution and also the concentration profilesnside the adsorbent particles, in the case where internal massransfer resistance is assumed. A general model was used forhe saturation step of the fixed-bed adsorber which includesore diffusion, film mass transfer resistance and axial disper-ion. The resulting partial differential equations (PDEs) wereumerically integrated with the PDECOL package, commercialoftware written in Fortran 90. To incorporate the computerrograms in the platform Matlab MEX-files that call the Fortranoutines were generated.
A case study involving the adsorption of phenol into a com-ercial adsorbent (DUOLITE ES-861) is proposed in order to
llustrate the effect of operating conditions, equilibrium andinetic parameters on the adsorption process efficiency. Theesults are shown in graphical or tabulated form.
Referring to the separation by ion-exchange, this applica-
ion is closely related to the Virtual Experiments section, sincehere is an experiment in this last section to study the uptakef an electrolyte in a column packed with a cation-exchange
rs 4 ( 2 0 0 9 ) e9–e19 e13
resin. In this case, the students will be able to integrate equip-ment design and performance analysis through simulation,with the visualization, either remotely or in the laboratory, ofthe phenomena studied. All of this can be performed throughthe web, without needing to be physically in the laboratory.
3.2. Chemical reaction
Chemical Reaction Engineering is intrinsically associated withSeparation Engineering, the performance of the overall pro-cess being dictated by the optimization of the total assemblyof units. Our main goal in the Chemical Reaction sectionfocuses on the development of e-learning tools in the fieldof kinetic studies and design and operation of reactors tobe used in homogeneous and heterogeneous processes. Asregards kinetics, the modelling analysis was associated withexperimental tests to determine kinetic parameters, reactionorders and activation energies in Arrhenius type equations.Both integral and differential methods were incorporated intothe simulators. In the context of reactor analysis, chemicalreactors with ideal behaviour, stirred tanks under continuous,batch and semi-batch operation as well as plug flow reac-tors are addressed. Afterwards, catalytic reactors are analysedwith particular emphasis on fixed-bed reactors largely usedin industry. In this domain, pseudo-homogeneous and het-erogeneous mathematical models were developed in steadystate regime, requiring different numerical techniques forcomputer simulation of the resulting ordinary differentialequations (ODEs) or algebraic and ordinary differential equa-tions (DAEs). These systems of equations were solved by usingvarious well-known Fortran codes, namely GEAR and DDASAC(Hindmarsh, 1974 and Stewart et al., 1991).
The analysis of the behaviour of such systems is based ontwo case studies involving the synthesis of phthalic anhydrideand formaldehyde through partial oxidation of ortho-xyleneand methanol, respectively. The analysis of these gas–solidsystems highlights the importance of the thermal instabili-ties whose occurrence is possible in such highly exothermicprocesses such as temperature runaway, extremely importantfor safety concerns. The catalyst particle itself may be alsoanalysed in detail, for the case of first order and irreversiblereactions under isothermal conditions in the catalyst.
The flow patterns in real chemical reactors are differentfrom ideal flow which is often considered at design stage.These deviations may lead to reactor performances that donot match the expectations or may even cause problemsduring operation. In the Residence Time Distribution (RTD)section the concepts and strategies used for characterizingand quantifying non-ideal flow are presented. Moreover, usingthe simulator available in this module, students can calcu-late and plot the response to pulse and step inputs of tracerin arbitrary systems, which are the experimental techniquesused to evaluate the RTD in open systems. The experimentalprocedure is also illustrated in one of the virtual experiments.
3.3. Process Systems Engineering
The area of Process Systems Engineering (PSE) developsmethodologies for systematic decision-making in chemicalprocesses, using a variety of mathematical tools and algo-rithms. Some of the activities that are usually associated
with PSE include modelling, simulation, integration, optimiza-tion, instrumentation and control, data reconciliation andproduct and process design. The main objective of the PSE
ngin
e14 education for chemical e
section is therefore to introduce the student to a variety ofproblems and methodologies that can be typically associ-ated to the development and manufacture of chemical relatedproducts (pharmaceuticals, novel materials, commodities andspecialties) and process operating modes (batch or continu-ous). To help the students acquire systematic problem solvingskills, interaction with classroom activities with teacher guid-ance is considered. During class, the students are exposedto systematic problem solving methodologies, for a numberof different problems. Afterwards, they can practise theseskills by interacting with the examples provided in the virtualplatform.
One basic module of the virtual platform includes a set ofexamples covering key concepts in the domain of instrumen-tation and process control. The instrumentation, sensors tomeasure and valves to influence the process conditions, isessential in the study of automatic control and supervisionof industrial processes. The static and dynamic character-istics of the sensors for measuring temperature, pressure,level and flowrate are illustrated by linking to a multimedialibrary prepared to assist the chemical engineering studentsto learn the industrial instrumentation used in most chemi-cal processes. For each type of sensor the following topics arecovered: operating principles, type of devices, static character-istics, calibration, selection, suppliers, costs, advantages anddisadvantages.
Moreover, sensors were installed outside the departmentbuilding to monitor outdoor air quality (SO2, NO2 and COemissions), as well as to measure temperature and relativehumidity in real time. Electrochemical sensors, a thermis-tor NTC and a capacitive hygrometer are used for themeasurements of gas emissions, temperature and humid-ity, respectively. A data acquisition system was implementedusing the LabVIEW® software, with data made availablevia LABVIRTUAL in the form of tables with numerical val-ues, and graphical displays of the day, week, month andyear. These data can be used in problems to be solvedby the students in classes of environmental engineeringcourses.
The students are also introduced to additional conceptsrelated to dynamic systems. Here, tutorial materials on fun-damental topics, descriptions of various problem-solvingmethodologies and interfaces to process simulators are avail-able, where the concepts learnt can be tested throughapplication to selected cases studies. The students can there-fore be exposed by simulation to real world situations thatotherwise would be difficult, expensive, lengthy or even dan-gerous to reproduce in a physical laboratory.
The physical examples considered are built starting fromsimple examples (like hydraulic systems), where most ofthe basic concepts of instrumentation and single-loop con-trol laws can be illustrated, to more advanced processes,through the gradual introduction of additional chemical andphysical phenomena, once the concepts described in othersections of the portal are mastered. Using this approach,important practical aspects such as the effects of the choiceof the sampling rate for discrete control, or the effects oferrors introduced by linearizing models at various operat-ing points, to the use of more advanced concepts such asalternative control strategies (adaptive and predictive), as wellas the setup of parameter estimation and system identifi-
cation schemes can be covered, in a modular form, alwayswith a very close link to reality and practical experimenta-tion.
eers 4 ( 2 0 0 9 ) e9–e19
One additional module in this section addresses the useof process integration and optimization methodologies inthe context of rationalization of energy and utility usage inthe process industries. The importance of developing sys-tematic methodologies (characteristic of the PSE approach)is stressed here, to develop sustainable and more environ-mentally friendly chemical processes. The students are firstexposed to the key concepts of interconnection efficiency inthe chemical processes, and learn the usage of simple graphi-cal tools to evaluate it and assess a range of process targets, byapplication of the pinch methodology. A simulator is provided,for fast determination of these efficiency targets, once thebasic concepts are mastered. Later, an alternative methodol-ogy to quantify these targets (based on applied mathematicaloptimization) is introduced, in order to increase the flexibilityof the approach.
Finally, this section also includes a subsection focused onProduct Engineering, which links to a more detailed web pagedeveloped by the University of Cambridge (Moggridge et al.,2008).
3.4. Biological processes
Day by day chemical engineers get more and more involved innon-traditional areas forcing the education in chemical engi-neering to evolve in order to correspond to the new needs andnew opportunities of the profession. Biochemical engineeringis closely related to chemical engineering in applying physicalprinciples to the resolution of biological processes. Sharinga common language with biological scientists is necessaryfor mutual understanding in an interdisciplinary coopera-tion. Modelling biological processes using theory, empiricalcorrelations and mathematical tools contributes to the under-standing of biological phenomena and, as a result, to betterdetermine process parameters and to predict the performanceof the equipment under different working conditions, etc.,always considering the properties of the biological entities.The predictive capacity of the mathematical models is par-ticularly useful for training and education, facilitating thedemonstration of phenomena in virtual experiments that oth-erwise would be expensive and lengthy in the lab. Such anapproach has been used in the platform for the quantitativeanalysis of biological kinetic data, to evaluate simple or morecomplex fermentations as affected by process conditions suchas cell density and growth rate, substrate concentration, airflowrate, dissolved oxygen concentration, stirrer speed, etc.Enzyme catalysis and the dynamics of enzyme reactors arealso covered.
The recovery of bioactive products is more constrained incomparison with the unit operations that are more traditionalin chemical engineering, in order to avoid loss of activity andcontamination by other products. At this stage only the basicprinciples of membrane and chromatographic processes havebeen considered. The simulation of the ultrafiltration process,in batch or continuous mode, can be tested as an examplefor illustrating the potentialities of membrane technology inseparating macromolecules. Regarding chromatography, thepartition of two components between a mobile and a sta-tionary phase (adsorbent) has been simulated by using thetechnique of elution chromatography, in which the sample isinjected into the column as a pulse. In both cases, the students
have the opportunity of testing key concepts involved in theseoperations and evaluating different operating approaches toachieve the best separation efficiency.
inee
3
Epntwfpp
KHHtadtinptFv
owtwctwtctTbuttddtvtbirttpdtd
aictortec
education for chemical eng
.5. Virtual experiments
xperimentation is as fundamental for the students’ learningrocess as theoretical knowledge. The inclusion of a sectionamed “Virtual Experiments” aims to meet this objective. Vir-
ual experiments is intended to be an independent section,ith links to other relevant areas of the site. In this way dif-
erent approaches for facilitating the learning and teachingrocesses in Chemical Engineering laboratories can be cou-led.
Four experiments are included here: Determination of theinetic Constant and Activation Energy for the Liquid Phaseomogeneous Reaction between Ethyl Acetate and Sodiumydroxide; Flow Pattern Characterisation in a Tubular Reac-
or Packed with Glass Beads; Study of the Sucrose Inversionnd Study of a Cation-Exchange Resin. In addition to theescription of the experimental setups and procedures andhe theoretical background for each work, multimedia supports provided in the form of a video, illustrating the compo-ents of each setup and the major steps in the operationrocedures and experimental occurrences. The experimen-al results collected and their treatment are also illustrated.inally, a template for a short report of each work is pro-ided.
In the section of process control, the students may carryut remotely one feedback control experiment, the setup ofhich is located in the Chemical Engineering Department of
he Faculty of Engineering of the University of Porto. Using theebserver capabilities of LabVIEW®, the experiment interface
an be accessed via a web browser and a webcam placed inhe laboratory captures live images of the experiment. Thisay the students will be able to experiment and have con-
act with the basic concepts of PID process control. The setuponsists of a cascade of two tanks in which the outlet fromhe bottom tank is recycled to the top tank using a pump.he purpose is to control the liquid level in the bottom tanky acting on the recycle valve. The user may operate thenit with the discharge of the top tank fully open, so thathere is no liquid accumulation in this tank and the sys-em becomes a single tank liquid level control, or have theischarge valve partially closed, originating more complexynamics and instability. Additionally, the user may chooseo introduce a simulated delay in the action of the controlalve, also introducing instability and demanding a carefuluning of the controller’s parameters. All the equipment cane activated through the remote interface, including switch-
ng on the recycle pump. The results of the experimentaluns can be stored in a text file that can also be accessedhrough the web browser. The site provides a description ofhe different elements in the interface, as well as an examplerocedure for conducting the remote experiment. This proce-ure illustrates offset elimination using integral control andhe instability caused when a delay in the valve action is intro-uced.
This remote experiment was originally conceived for uses a local setup. However, some of its characteristics madet well suited for remote access. In particular, it is intrinsi-ally safe, not needing continuous human supervision andhe system’s response time is short, allowing for results to bebtained in a relatively short time, which is important whenemote operation is intended—30 min to 1 h is sufficient for
esting the system’s behaviour for different sets of PID param-ters. In addition the setup may be used for practicing differentontroller tuning strategies.
rs 4 ( 2 0 0 9 ) e9–e19 e15
At a later point of the project, a lab report management anda verification tool will be developed. This will include, amongother features, e-mail report delivery management, valida-tion of lab results, computation of parameters from reporteddata, comparison between the “expected” parameters and thereported ones.
4. Using the virtual platform to teachchemical processes
The platform described above is mainly oriented towardsteaching Chemical Processes, in the aforementioned fields,at graduation level (both 1st and 2nd cycles according to theBologna scheme), though the portal also includes other fea-tures. In fact, in the future there will also be applicationsdirected towards lifelong learning and to the lower school lev-els outreach. In this section of the paper we will discuss onlythe use of the platform for teaching at graduation level (1stand 2nd cycles).
According to the philosophy behind its construction, thesite can be used in the classroom to illustrate the designand operation of process equipment, for instance to show theinfluence of operating conditions, feed characteristics, etc., onthe design outcome, or even to evaluate the validity of differ-ent models in order to do the design.
After this first contact with the facilities of the platform ina course, the student can go on using the site on her/his own,taking advantage of the case studies included there, with theaim of illustrating the phenomena described in the fundamen-tals section, as well as to solve new problems. Furthermore,the student can use the available tools to solve other assign-ments (design problems) or even, at a later stage, use modulesof the simulators to build more complex programs requiredto work through complex design problems, for instance in thesenior design project.
A prototype of the platform has already been in use overthe last two academic years, for the teaching of Distillationin the Chemical Engineering curriculum from the Universityof Coimbra (Rafael et al., 2007). The first stage of the fullintegrated platform has just been finalized and the differentapplications are now starting to be used in different courses.
So far the portal has been introduced to students of at least11 courses in the Chemical Engineering curricula at both theUniversities of Coimbra and Porto such as Transport Phenom-ena (1), Chemical Thermodynamics (1), Reaction Engineering(2), Process Separations (2), Control Engineering (2), Biologi-cal Processes (1) and Integrated Problems (2). Depending onthe characteristics of the course, the use of the platform canbe optional or compulsory. Moreover, the students have beenusing it not only for autonomous study but also to solve home-work assignments. In some of the courses programming skillsare also integrated: for instance, in mini-projects, studentshave to modify the current simulators for other applicationsand/or conditions.
In this section of the paper we will next describe threeexamples of the use of the platform in different areas of Chem-ical Engineering: Liquid–Liquid Extraction, Chemical Reaction(more precisely the determination of the kinetic parametersof a reaction—reaction orders and activation energy) and, con-cerning Biological Processes, a simple design of an enzymatic
reactor. Referring to the first example we will also describethe use of the modules for liquid–liquid equilibrium predictionincluded in the Thermodynamics section. As for the chemical
ngineers 4 ( 2 0 0 9 ) e9–e19
Fig. 3 – Liquid/liquid equilibrium diagram for a multistage
e16 education for chemical e
reaction kinetics example we will illustrate how, in the plat-form, we integrate simulation with the virtual experiments.
4.1. Liquid–liquid extraction
The design of a multistage liquid–liquid extraction process,both using a battery of mixing/settling tanks or a counter-flowcolumn, can be based on the concept of theoretical stage, cor-responding to thermodynamic equilibrium between the twoimmiscible liquid phases, which is then corrected to describereal operating conditions. Therefore, prior to using designmethods, students should be familiar with the basics and cal-culations of liquid–liquid equilibrium (LLE).
Given a global initial composition, the LLE simulator inthe LABVIRTUAL portal solves the equilibrium relationshipsfor the different species together with mass balances, theresult being the composition of the two liquid phases in equi-librium. The activity coefficients of the different species inthe two liquid phases are estimated by the UNIFAC groupcontribution method (Magnussen et al., 1981). The simulatorperforms calculations for mixtures with two to five compo-nents, chosen from a set that, for the time being, only has sixchemicals. The different combinations can, however, illustrateseveral typical situations with different mutual solubilities(e.g. water + hexane + ethanol with water and hexane practi-cally immiscible and ethanol with a great preference to theaqueous phase; water + ethyl acetate + ethanol with the firstpair being partial miscible and ethanol more equally dis-tributed between the two phases).
Let us here consider the system water (A), diisopropylether(B) and acetic acid (C), with the ether being the solvent usedto extract the acid from an aqueous solution. Table 1 com-pares predictions made using the LLE simulator and availableexperimental data (Treybal, 1980), for two different initial com-positions (wF). Predictions are very reasonable in the caseof a low acid concentration and fail for higher concentra-tions, namely by underestimating the distribution coefficient(wC,E/wC,R) and the amount of ether present in the residue.By varying the initial composition (wF), the complete ternarydiagram may be drawn and compared with the experimentalone.
The Extraction simulator can be applied to the design ofa counter-flow continuous column with N theoretical stages,one feed stream (F, introduced in stage 1) and one solventstream (S, introduced in stage N). Only the simplest case ofA and B being immiscible is handled. The user specifies thestreams F and S and the recovery of solute in the final extract
or, alternatively, the number of stages. The equilibrium datamust also be provided in the form of a polynomial correla-
Table 1 – LLE predictions and experimental values for thesystem water (A), diisopropylether (B) and acetic acid (C).
w is mass fraction; F, R and E designate, respectively, the initialmixture (feed), residue and extract; experimental values are fromTreybal (1980), at 20 ◦C and 1 atm.
extraction column (X, mass of C/mass of A and Y, mass ofC/mass of B).
tion wC,E = f (wC,R), where wC,E is the solute (C) mass fractionin the extract, only composed of (B + C) and wC,R is the solutemass fraction in the residue, only composed of (A + C). Thecorrelation may be based on available experimental data orpredictions.
For the system considered here, a design based on theunderlying assumptions described above would be reasonablefor an acid mass fraction in the initial mixture up to about 0.1.However, since experimental data are available (Treybal, 1980),we use them to construct the correlation wC,E = 0.70828w2
C,R +0.26376wC,R − 0.00028492, valid for wC,R < ∼0.26, where theA/B immiscibility assumption is still reasonable. The feedand solvent streams are as follows: F = 100 kg/h, S = 200 kg/h,wC,F = 0.3 and wC,S = 0.01, with these two last variables beingsolute mass fractions, respectively, in the feed and solventstreams. For an 80% recovery, the composition diagram inFig. 3, based on the McCabe-Thiele method, is obtained, com-prising 7 equilibrium stages. X and Y represent the mass ratiosof solute in the residue and extract (X stands for mass ofC/mass of A and Y for mass of C/mass of B). Besides theoperating and equilibrium lines, the diagram also shows theoperating line for the minimum solvent flowrate, which in thiscase is 155 kg/h. Starting from a base case, students can easilystudy the impact of several variables, including feed composi-tion, solvent flowrate or solvent purity. In this example, due tothe shape of the equilibrium line and also the solvent contami-nation with solute, recoveries above 90% are hard to obtain. Anincrease in solvent purity would offer a significant improve-ment: for wC,S = 0.001, and keeping the same number of stagesand the same solvent flowrate, the recovery increases to 85%.
This example clearly shows how the portal can be usedto facilitate the integration by the user of different subjectsand disciplines of Chemical Engineering. Liquid/liquid equi-librium, addressed in the first part of the example, is a chapterof the Chemical Thermodynamics course, while liquid/liquidextraction is addressed in the Transfer and Separation Pro-cesses course. When using the portal the student is directedto integrate these two subjects (addressed in different disci-plines) in a natural way.
4.2. Kinetic studies
The estimation of the kinetic parameters is often addressedin the curricula of chemical engineering based on the liquidphase homogeneous reaction between ethyl acetate (EAc) and
education for chemical engineers 4 ( 2 0 0 9 ) e9–e19 e17
Fig. 4 – (a) Fitting of the experimental values for the hydrolysis of ethyl acetate using the integral method, when n = m = 1. (b)F
sewsa
r
wfiasmseomnfiotsef
l
whN
Flactcp
ectoi
t
itting of the Arrhenius equation.
odium hydroxide (NaOH). As referred above, this laboratorialxperiment can be found in the Virtual Experiments section,here a video is available in order to show the experimental
etup and procedures. The reaction rate, r, may be considereds:
= kCnNaOHCm
EAc (1)
here k is the kinetic constant, n and m are the partial ordersor sodium hydroxide and ethyl acetate, respectively; CNaOH
s the sodium hydroxide concentration and CEAc is the ethylcetate concentration. This reaction is carried out in a batchtirred reactor at 15, 20 and 25 ◦C, and the students may deter-ine, using the simulator in the Chemical Reaction Processes
ection, the partial orders (n, m) based on the integral or differ-ntial method. When choosing the integral method, the partialrders must be settled a priori and the following combinationsay be tested in the simulator: n = 0 and m = 0; n = 1 and m = 1;= 1 and m = 0; n = 0 and m = 1; n = 1.5 and m = 1.5. In order tot the known concentration profile of NaOH, the conversionf this reagent was used to relate the concentrations of thewo reagents and to allow integration and linearization. Thetudents can understand the consequence of admitting differ-nt values for n and m. For example, considering n = m = 1, theollowing equation is fitted by the simulator (r = −dCNaOH/dt)
n(
M − xNaOH
M(1 − M − xNaOH)
)= kCNaOH,0(M − 1)t (2)
here M corresponds to CEAc,0/CNaOH,0, xNaOH is the sodiumydroxide conversion, CNaOH,0 is the initial concentration ofaOH, k is the kinetic constant and t is the time.
By representing the experimental data as indicated inig. 4(a) when the temperature of the system is set at 15 ◦C, theinear fitting is the one indicated through the solid line, with
coefficient of correlation, R2, equal to 0.999. The studentsan conclude that the orders n = m = 1 are adequate trials, andhat the kinetic constant is 5.28 × 10−5 m3 mol−1 s−1. For eachase, the user may also validate the model by comparing theredicted values with the experimental ones.
Since no experiments were performed at the conditions ofxcess of reagent, the differential method is limited to thease of n = m; otherwise the linearization is not possible. Forhis particular case (n = m), students may compare the fittingbtained with this method with the one obtained through the
ntegral method.Another important analysis that may be performed with
he platform concerns the prediction of the activation energy,
E, and the pre-exponential factor, k0, by using the Arrheniusequation. After knowing the kinetic constant calculated at 15,20 and 25 ◦C, the students may obtain a similar fitting to theone represented in Fig. 4(b). In this case, one may concludethat the hydrolysis of the ethyl acetate, in the range of tem-peratures tested, is characterized by an activation energy (E)equal to 4.79 × 104 J mol−1 and k0 = 2.58 × 104 m3 mol−1 s−1.
It should be stressed that besides the described simulationsand the possibility of viewing the video corresponding to thisexperiment on the platform, the students will always performthis experiment in the laboratory as well. The analysis of theresults for reporting may be done using the simulators, whichoffer the capability to test different aspects of this reaction ina very efficient way.
4.3. Biological processes
Enzyme immobilization is important for reuse or continuousoperation. An enzyme can be either adsorbed onto the surfaceor entrapped within an inert support, where it is subjected tointernal and/or external mass transfer limitation. This supportcan be a particle or a membrane.
In the portal, experimental data can first be processed in asimulator to determine the kinetic parameters KM and Vmax,assuming a Michaelis–Mentel model and a Lineweaver–Burkrepresentation of the data (Bailey and Ollis, 1986).
The expressed enzyme activity depends on the geometryof the supporting medium. If the enzyme is homogeneouslyentrapped within a spherical particle of radius R, suspendedin a substrate solution, the substrate has to overcome first anexternal barrier and then an internal resistance to diffusioninto the particle through a concentration gradient. The sub-strate concentration is always lower than in the bulk solutionand, therefore, the reaction rate decreases in the radial direc-tion towards the centre. The overall reaction rate can thus berelated to what the reaction rate would be if the enzyme wasin solution, through an overall effectiveness factor, �ov
e , whichcan be calculated as the product, �ov
e = �ee × �ei, of an externaleffectiveness factor, �ee, and an internal effectiveness factor,�ei. If the immobilized enzyme preparation is used in a contin-uous stirred tank reactor, the working volume of the reactor(V) can be calculated knowing the imposed flow, F, for a pre-determined productivity and the residence time tCSTR to reacha given conversion of the substrate.
From a mass balance,
tCSTR = V
F= (Se − Ss)(KM + Ss)
�ove VmaxSs
(3)
e18 education for chemical engineers 4 ( 2 0 0 9 ) e9–e19
: (a)
Fig. 5 – Portal assessment
where Se and Ss are the substrate concentrations in the feedand the out-leaving solution, respectively.
For the calculation of �ove the external effectiveness factor
can be calculated using the equation
�ee = (ˇb − ˇi)(1 + ˇb)Daˇb
(4)
where Da is the Damkohler number, Da = Vmax/KLaKM, ˇb =Ss/KM, (1/Da)(ˇb − ˇi) = ˇi/(1 + ˇi), KL is the mass transfer coef-ficient and a is the specific interfacial area of the beads; thesubscripts b and i refer to the bulk medium and the particleinterface with the bulk liquid.
The internal effectiveness factor, �ei, is calculated usingthe Moo-Young and Kobayashi equation (Moo-Young andKobayashi, 1972): �ei = (�i0 + ˛�i1)/(1 + ˛), where ˛ = KM/Ss,and �i1 and �i0 are the internal effectiveness factors for zeroand first order reactions, respectively.
Both the external and the internal effectiveness factors canbe obtained from two separate simulators inside the enzy-matic reactors module.
Using the same data the substrate concentration profile canalso be determined in another separate simulator.
5. Assessment of the portal
The Chemical Engineering Integrated Master’s in the Chemi-cal Engineering Department of the University of Coimbra, hasa numerus clausus of 45 students every year (a total of about300 students in the 5-year course). However, the portal is not
limited to those students. During the 2 months (April and May2008) when the portal was totally open, after being made pub-lic, between 2300 and 5700 people/month visited it. Since then,
questionnaire; (b) results.
visits to the Simulators, to the Virtual Experiments and to theChemical Processes sections needed registration and identi-fication. Despite that, in September, October and Novemberabout 1100 people/month visited the portal.
Although a complete evaluation of the portal is not yetpossible, two anonymous questionnaires have already beenfilled out to obtain the students’ evaluation: one at the end ofMay in the course of Transfer and Separations Processes I, andthe other at the beginning of December 2008 in the course ofTransformation Processes I, involving about 60 students. Thequestions addressed different aspects of the learning expe-rience, students’ frequency and purpose of use, as well asthe evaluation of the interface and the structure of the por-tal (Fig. 5a). The students’ responses were very positive ascan be seen in Fig. 5b, with the majority classifying the portalas “useful” or “very useful”, and “well” or “very well” struc-tured. Almost all of them had used the platform in the referredcourses, whereas 80% had used it in five other subjects. Themajority of the students had used the portal as a supportto their study (65%) or for project design (70%). Among therespondents, the general rate achieved by the portal was D(good) and E (very good) on a five-point scale.
6. Conclusions
The portal LABVIRTUAL (http://labvirtual.eq.uc.pt) is a valu-able tool for the teaching of Chemical Processes because ofseveral features which are usually not combined in a singleplatform:
- Existence of a multimedia library for the different processes,which includes links to many other references and web
pages, which can be used by the students during their self-study learning process.Simulators (twenty in total) which enable designing anddimensioning the different processes addressed, leading thestudents to understand the correlation between the operat-ing conditions of the process and the design output.Applications and case studies to help the students in theuse of the simulators and give them a practical perspectiveof the basic concepts.Virtual experiments which enable the students to visual-ize some basic phenomena and mechanisms on which thedesign of chemical processes is based, and also help thestudents to be better prepared to enter the Real laboratory.A broad collection of chemical processes addressed inthe same platform, in the different areas of ChemicalEngineering (Unit Operations and Separations, ChemicalReaction, Process Systems Engineering and Biological Pro-cesses), which are seldom combined in the same webapplication.
These features contribute to give the student an integratedpproach to Chemical Processes, leading them to an eas-er integration of knowledge which is addressed in differentourses.
Moreover, the portal has also been constructed withhe objective of disseminating information about Chem-cal Engineering to the general public, and mainly totudents in the basic and secondary education lev-ls.
Finally, and because the language of the portal is Por-uguese, it is expected that it can be used to strengthen theelations between universities in Portugal and their counter-arts in the Portuguese speaking countries, involved in theeaching of Chemical Engineering.
cknowledgment
he authors would like to acknowledge the sponsorship fromOSC (Programa Operacional da Sociedade de Conhecimento,ortugal), contract 743/4.2/C/REG which enabled the develop-ent of the platform described in this paper.
Kadiyala, M. and Crynes, B., 2000, A review of literature oneffectiveness of use of information technology in education. JEng Ed, 89(2): 177–189.
Klein, A. and Wozny, G., 2006, Web based remote experiments forchemical engineering education—the online distillationcolumn. Trans IChemE, part D, Educ Chem Eng, 1: 134–138.
Magnussen, T., Rasmussn, P. and Fredenslund, A., 1981, UNIFACparameter table for prediction of liquid–liquid equilibria. IndEng Chem Process Des Dev, 20: 331–339.
Mendes, A.M.M., (2002). Laboratórios de Engenharia Química. (FEUPEdicões, Porto).
Moggridge, G.D., Saraiva, P.M. and Costa, R., 2008, ChemicalProduct Design Teaching,http://www.engsc.ac.uk/an/mini projects/cpd/index.html,Accessed January 2008.
Molzahn, M., 2004, Chemical engineering education in Europe:trends and challenges. Chem Eng Res Des, 82(A12): 1525–1532.
Moo-Young, M. and Kobayashi, T., 1972, Effectiveness factors forimmobilized-enzyme reactions. Can J Chem Eng, 50: 162–167.
Rafael, A.C., Bernardo, F., Ferreira, L.M., Rasteiro, M.G. andTeixeira, J.C., 2007, Virtual applications using a web platformto teach chemical engineering: the distillation case. TransIChem, Part D, 2: 20–28.
Rasteiro, M.G., Carvalho, M.G.V.S., Baptista, C.M.S.G., Ferreira, A.and Granjo, J., 2008, Using a web platform to the teaching ofchemical processes for secondary school students outreach,Proc. ICEE 2008, Pecs, Hungary, July.
Selmer, A., Kraft, M., Moros, R. and Colton, C.K., 2007, Weblabs inchemical engineering education. Trans IChemE, part D, EducChem Eng, 2: 38–45.
Stewart, W.E., Caracotsios, M. and Sørensen, J.P., (1991). Softwarepackage documentation of DDASAC—Double Precision DifferentialAlgebraic Sensitivity Code. (University of Wisconsin-Madison,EUA).
Streicher, S.J., West, K., Fraser, D.M., Case, J.M. and Linder, C.,2005, Learning through simulation—student engagement.Chem Eng Ed, 39(4): 288–295, 301
