- Email: [email protected]
Supporting the use of PSE computational tools across a chemical engineering program
Mario R. Eden, Marianthi Ierapetritou and Gavin P. Towler (Editors) Proceedings of the 13th International Symposium on Process Systems Engineering – PSE 2018 July 1-5, 2018, San Diego, California, USA © 2018 Elsevier B.V. All rights reserved. https://doi.org/10.1016/B978-0-444-64241-7.50270-6
Supporting the use of PSE computational tools across a chemical engineering program Mazaher Molaei Chalchooghi and Eva Sorensen* Department of Chemical Engineering, UCL, Torrington Place, London, WC1E 7JE, UK * [email protected]
Abstract The use of Process Systems Engineering (PSE) computational tools across a chemical engineering curriculum is now an expectation rather than an exception, but may be challenging to deliver in a consistent and meaningful manner across an entire program. The Department of Chemical Engineering at UCL offers a variety of computational tools across our undergraduate programs, including MATLAB, GAMS, gPROMS ModelBuilder and ASPEN Plus. All modules across the program are expected to provide at least parts of the assignments in the form of PSE problems requiring the use of computation tools, often formulated in such a way that the students have a choice of tool to use. Our extensive use of computational tools is made possible by a dedicated faculty member whose sole responsibility is the development and delivery of regular lecture and tutorial material, support with assignments, as well as the development and maintenance of e-learning resources. In addition, we also have dedicated teaching assistants for each module who have domain expertise in the relevant tools, and who assist with tutorials and marking of assignments. Student feedback has shown that students highly value the extensive training in these commonly used tools, and that their leaning experience is made relevant by the application of challenging PSE problems. Keywords: Engineering education, process systems engineering, computational tools, e-learning
1. Introduction Computational tools are now used extensively in most, if not all, chemical engineering programs. Most core modules or courses require some use of computational tools, from solving simple algebraic equations or complex differential equations systems, to plant design, control or optimization. Depending on the type of problem, and the licenses held by the department, the student can choose the most suitable tool from a variety of available commercial packages such as Excel, MATLAB, C++, Python, gPROMS, ChemCAD, ASPEN Plus etc. The Department of Chemical Engineering at UCL offers both Bachelor and Masters programs in Chemical Engineering through its Integrated Engineering Programme (IEP) (Sorensen, 2016), with around 120-150 students per cohort. The IEP is a Faculty-wide, multidisciplinary program which combine core disciplinary technical knowledge with interdisciplinary and/or research-based projects with strong emphasis on professional skills and academic learning connected with workplace learning. The program enables students to understand the fundamentals of their discipline, to practice the application of their core technical knowledge and to apply this to current complex global challenges such as energy, health etc. This focus on problem and/or project-based learning starts in Year 1 and continues throughout the program. For each project, the students will be
1652
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working in teams of 6-8 students in solving an open-ended and complex problem. In Year 1, students will consider two five-week Engineering Challenges, which are considered alongside their other modules. Later in the year, and in Year 2, we suspend all other teaching for a week and work fulltime on a specific problem that is linked to the modules the students are currently studying. In total, six such scenarios are considered. In addition to providing practical examples of real-life problems within mass & heat transfer, thermodynamics, separation processes, reaction engineering etc., the scenarios also help develop the students’ transferable skills such as team working, presentation, technical writing and time management as well as their professional skills in terms of understanding of, for instance, ethics, safety and sustainability. One of the main aspects of the IEP is a strong emphasis on modelling and design, with two compulsory module or classes dedicated to mathematical modelling & analysis for all Faculty of Engineering Sciences programs in Years 1 and 2. The department continues this with another module on computational modelling & analysis in addition to a number of other modules through Years 2-4 (see Table 1). With this approach, the use of computational tools is embedded within the curriculum and within the individual modules. The students learn to solve problems based on traditional approaches, such as McCabe-Thiele diagrams, but also learn how to set up and run Aspen Plus simulations of standard unit operations, and more importantly, how to critically evaluate the results based on the assumptions made in the definition of the problem. As for most UK programs, most modules are compulsory in Years 1-3, and are taken by the entire cohort at the same time. It is therefore possible to properly plan the use of a tool to ensure the material is introduced at the right time and that there is a clear progression from one module to the next or from one year to the next.
2. Integrating computational tools in undergraduate programs The main computational tools used within our program are: MATLAB - for general purpose computation, GAMS - for solving algebraic equation systems and optimization, gPROMS ModelBuilder - for custom modelling of steady-state or dynamic mixed algebraic and differential equations, and Aspen Plus - for process flowsheeting and plant design. Other computational tools are mainly used for research in Year 4 such as ANSYS Fluent and STAR-CCM+ for computational fluid dynamics, and DynoChem scale up for process development. Each tool is introduced in an introductory lecture that outlines the main capabilities of the tool, its usage in the chemical industries and beyond, as well as its basic features. The lecture is followed by one or more tutorials in a large cluster room where the cohort is split into smaller groups from 30 to 70 students. The tutorials are essential to ensure the students are able to first set up a basic problem and then gradually work though a number of problems of increasing complexity. The lecture is given by a dedicated faculty member who has extensive knowledge of each tool. The same person runs the tutorials but now supported by a number of teaching assistants, usually PhD students who are using the tool in their own research.
Use of PSE computational tools across a chemical engineering program
1653
Year 4 (Senior)
Year 3 (Junior)
Year 2 (Sophomore)
Year 1 (Freshman)
Table 1. Chemical engineering program at UCL (modules in grey are based on modeling and make explicit use of computational tools).
Term 1 Engineering Challenges Design & Professional Skills I Mathematical Modelling & Analysis I Introduction to Chemical Engineering Design & Professional Skills II Mathematical Modelling & Analysis II Engineering Experimentation Process Heat Transfer Separation Processes I Process Design Project Process Dynamics & Control Chemical Reaction Engineering II Minor II Research Project Process Systems Engineering & Design Elective Elective
Term 2 Transport Phenomena I Thermodynamics Physical Chemistry Computational Modelling & Analysis Design & Professional Skills II Mathematical Modelling & Analysis II Particulate Systems & Separation Processes II Chemical Reaction Engineering I Minor I Process Design Project Transport Phenomena II Advanced Safety & Loss Prevention Minor III Research Project Elective Elective Elective
Extensive additional resources are available as e-learning resources and cover all the aspects of modelling that the students may encounter in their homework assignments and examinations, for instance, heat exchanger networks, column scheduling, pump sizing etc. The resources are mainly in the form of pdf versions of Powerpoint presentations and are available on the student intranet via Moodle to all students, researchers and staff within the department. Each module also has a dedicated Moodle site, with a dedicated Question & Answer Forum where students can ask questions related to the computational tool or their assignments, and where answers are provided by the teaching faculty to the entire cohort. If additional support is needed, which is very often the case, this is arranged on an as-and-when basis in the form of helpdesk sessions in a smaller computer cluster, again by the same faculty staff. The students can sign up for these via the relevant Moodle site. 2.1. MATLAB MATLAB (Mathworks, 2017) is introduced to all Faculty of Engineering Sciences students in the first compulsory Mathematical Modelling & Analysis module in the first term. The module is taught by a number of academics from across the Faculty, with a weekly 2 hr Faculty lecture followed by a weekly 2 hr tutorial in the home department. The focus is very much on engineering problems, which by their nature can be described by a set of algebraic and/or differential equations. The students learn how to formulate the problems as well as the mathematical concepts required in solving them.
1654
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Whilst the lecture presents examples from across all engineering disciplines, the tutorials are based on problems from within the discipline. MATLAB is used for a number of the assignments hence support needs to be available for nearly 800 students. This is provided at Faculty level involving teaching staff, but also a large group of specially trained teaching assistants. The use of MATLAB is continued in the second year in Mathematical Modelling & Analysis II, which runs over the entire academic year with a 2 hr lecture at Faculty level one week and a 2 hr tutorial in the home department the following week. In addition to the compulsory use of MATLAB in these two modules, students may use MATLAB in other assignments throughout their program, for instance in the design of reactors in Chemical Reaction Engineering or for detailed unit design in their capstone Design Project in Year 3. Support is provided by the department in the form of helpdesk sessions for such work but only at the request from students. 2.2. GAMS The first Mathematical Modelling & Analysis module is followed by Computation Modelling & Analysis which is taught in the department and which follows on from the first module by demonstrating how larger systems of equations can be solved by computation tools rather than by hand or using MATLAB. The module is taught in two weekly two hour lectures with tutorials in addition some weeks. GAMS (GAMS, 2017) is introduced first and is used to solve steady-state problems consisting of a number of algebraic equations. The students are given assignments which must be completed as a combination of hand-calculations, Excel spreadsheets and using GAMS. Examples are to solve the mass balances on the form A x = b for a three column systems used to separate benzene, styrene, toluene and xylene, or to maximize the profit for a gas phase reaction system consisting of a mixer, a reactor, two separation units and a recycle stream. As for MATLAB, students may also use GAMS whenever they prefer for other assignments throughout their program. 2.3. gPROMS ModelBuilder The department has used gPROMS (Process Systems Enterprise, 2017) in undergraduate teaching for about 15 years. Until four years ago, gPROMS was only taught in Year 4 as part of our advanced design project. With the introduction of the Integrated Engineering Program (IEP), it was decided to use gPROMS from Year 1 and to cover increasingly complex aspects of the tool term by term and year by year. gPROMS is now introduced in the second part of Computational Modelling & Analysis and is used to solve sets of differential and algebraic systems. Again, the students are given assignments which must be completed as a combination of hand-calculations and using gPROMS. An example is to solve a set of differential equations which describes an aquatic ecosystem and to analyze how pollutants have an impact on water, plants, soil and fish. The use of gPROMS is continued in Year 2, and is incorporated into the two modules considering separation processes. In the first module, students use the tool to investigate the dynamic performance of, for instance, a distillation column stage subject to different disturbances. The students need to simulate and explain the dynamic responses based on their fundamental knowledge of volatility and mass balances for distillation. In the second separation module, students solve a problem related to Acetylsalicylic Acid (ACA) crystallization from Ethanol solution with a continuous MSMPR process. They
Use of PSE computational tools across a chemical engineering program
1655
are free to choose which modelling tool they prefer and many use gPROMS for this instead of MATLAB or GAMS. In Year 3, students consider Process Dynamics and Control, and again use gPROMS to investigate the dynamic behavior of a common unit operation such as a distillation column or a reactor. In Chemical Reaction Engineering, students solve a number of reactor design problems and many use gPROMS for this. The fourth year advanced design project, Process Systems Modelling & Design, builds on the capstone project in Year 3 and considers more advanced design issues such as dynamics, optimization and design under uncertainty. gPROMS is the main tool for this and students consider different design options for a given process, for instance styrene production, and determine the optimal design for both a reaction section and a separation section. They investigate the impact of the main design parameters, such as reactor temperature, scheduling of the distillation columns etc., and they consider the open-loop performance of the plant from both a safety and a production point of view and also propose a suitable control scheme for the overall plant. Some of students will also use gPROMS in their final year research project. gPROMS is the computational tool of choice for the department due to its robust capabilities in simulating large and complex equation systems, but more importantly because it is an easy tool to introduce students to, the learning curve is not too steep and it is easy to introduce the tool in bitesize portions throughout the program. 2.4. ASPEN Plus ASPEN Plus (Aspentech, 2017) is the other main tool used in our program. The students are introduced to the tool in Year 2 and will solve small design problems in each of the two separation modules, e.g. designing a distillation column and consider the impact of tray efficiency on the design. The tool is used extensively in the capstone design project in Year 3, and in the advanced design project in Year 4, for flowsheeting and individual unit design. Some students will also use ASPEN Plus in their research projects. 2.5. Use of computational tools in Scenarios and research-based work In addition to the regular modules and the assignments required for these, students also make extensive use of computational tools in the six week-long scenarios which run throughout Years 1 and 2. The open-ended problem descriptions are generally written in such a way that the students have a choice of which tool to use, which better mirrors the experience they will have as practicing engineers. All Masters’ students will undertake a research project in their final year, and the majority of them will use a computation tool for this. In addition to the main tools mentioned above, they may also make use of tools developed in-house or more advanced tools such as STAR_CCM+ for CFD simulations.
3. e-learning Resources Although all our computational tools are introduced and taught in formal lectures as well as supported by tutorials, extensive e-learning resources are also provided to further support the students as all the nuances and details of a computational tool cannot be conveyed in the form of lectures/tutorials. The e-learning material has been developed mainly in-house and aims to lead the students through different examples and to teach them different aspects of the tools that have not been fully covered during the face-to-face sessions. As an example, for ASPEN Plus we do not cover the detailed use
1656
M. Molaei and E.Sorensen
of all the available unit operations during the lectures/tutorials, but rather we give the students a brief overview in the face-to-face sessions and leave the details to the eleaning material. We update the e-Learning material every year based on what we experience as being difficult for the students, as well as based on direct student feedback. The development of the e-learning material has primarily been done through student summer internships which we have run for three summers with a number of undergraduate students every year. This approach has worked well, as the student interns know better than teaching staff what they themselves found difficult and where more help and support is required.
4. Discussion The use of Process Systems Engineering (PSE) tools across a chemical engineering curriculum may be challenging to deliver in a consistent and meaningful manner across an entire program. First and foremost, faculty that are experienced in the use of the tools is essential, as is teaching assistants with a good working knowledge. Secondly, there is a balance between teaching the tool via lectures and tutorials, based on student selfstudy using e-learning resources and books, or as a combination. There is generally limited time available on the time table to provide in-depth training, and there is often an expectation that tools such as MATLAB or ASPEN Plus are easy to pick up and require little support, however, from a student perspective, these tools are not intuitive and are often a challenge to learn, particularly for weaker students. As a result, the use of PSE computational tools are often not considered as widely as they could, and should, be. Our decision to have a faculty member dedicated to the support of computational tools has not only provided a much better service to our students but has also reduced the workload on colleagues who now receive proper help to formulate their PSE related assignments. One final year student comments: “Across the years I have been at UCL I have been able to see the changes that has been made, and the course has definitely improved. It is particularly noticeable when looking at … and the quality and frequency of programming tutorials.”
5. Conclusion The use of computational tools in a chemical engineering undergraduate program at UCL has been presented. All the main tools are directly embedded into the curriculum and are supported by lectures, tutorials and e-learning resources. This is made possible by a dedicated faculty member who delivers all the training across the program, who works with colleagues in integrating the use of PSE problems and tools, and who supports the students directly in their work.
6. References Aspentech, 2017, http://home.aspentech.com/products/engineering/aspen-plus (viewed Dec 1, 2017) E. Sorensen, 2016, Changing the World – Educating students differently with a more scenario and problem-based engineering curriculum, The Chemical Engineer, 904, 27-31. GAMS, 2017, https://www.gams.com/ (viewed Dec 1, 2017). Process Systems Enterprise, 2017, https://www.psenterprise.com/products/gproms (viewed Dec 1, 2017). Mathworks, 2017, https://www.mathworks.com/products/matlab.html (viewed Dec 1, 2017).
Supporting the use of PSE computational tools across a chemical engineering program Mazaher Molaei Chalchooghi and Eva Sorensen* Department of Chemical Engineering, UCL, Torrington Place, London, WC1E 7JE, UK * [email protected]
Abstract The use of Process Systems Engineering (PSE) computational tools across a chemical engineering curriculum is now an expectation rather than an exception, but may be challenging to deliver in a consistent and meaningful manner across an entire program. The Department of Chemical Engineering at UCL offers a variety of computational tools across our undergraduate programs, including MATLAB, GAMS, gPROMS ModelBuilder and ASPEN Plus. All modules across the program are expected to provide at least parts of the assignments in the form of PSE problems requiring the use of computation tools, often formulated in such a way that the students have a choice of tool to use. Our extensive use of computational tools is made possible by a dedicated faculty member whose sole responsibility is the development and delivery of regular lecture and tutorial material, support with assignments, as well as the development and maintenance of e-learning resources. In addition, we also have dedicated teaching assistants for each module who have domain expertise in the relevant tools, and who assist with tutorials and marking of assignments. Student feedback has shown that students highly value the extensive training in these commonly used tools, and that their leaning experience is made relevant by the application of challenging PSE problems. Keywords: Engineering education, process systems engineering, computational tools, e-learning
1. Introduction Computational tools are now used extensively in most, if not all, chemical engineering programs. Most core modules or courses require some use of computational tools, from solving simple algebraic equations or complex differential equations systems, to plant design, control or optimization. Depending on the type of problem, and the licenses held by the department, the student can choose the most suitable tool from a variety of available commercial packages such as Excel, MATLAB, C++, Python, gPROMS, ChemCAD, ASPEN Plus etc. The Department of Chemical Engineering at UCL offers both Bachelor and Masters programs in Chemical Engineering through its Integrated Engineering Programme (IEP) (Sorensen, 2016), with around 120-150 students per cohort. The IEP is a Faculty-wide, multidisciplinary program which combine core disciplinary technical knowledge with interdisciplinary and/or research-based projects with strong emphasis on professional skills and academic learning connected with workplace learning. The program enables students to understand the fundamentals of their discipline, to practice the application of their core technical knowledge and to apply this to current complex global challenges such as energy, health etc. This focus on problem and/or project-based learning starts in Year 1 and continues throughout the program. For each project, the students will be
1652
M. Molaei and E.Sorensen
working in teams of 6-8 students in solving an open-ended and complex problem. In Year 1, students will consider two five-week Engineering Challenges, which are considered alongside their other modules. Later in the year, and in Year 2, we suspend all other teaching for a week and work fulltime on a specific problem that is linked to the modules the students are currently studying. In total, six such scenarios are considered. In addition to providing practical examples of real-life problems within mass & heat transfer, thermodynamics, separation processes, reaction engineering etc., the scenarios also help develop the students’ transferable skills such as team working, presentation, technical writing and time management as well as their professional skills in terms of understanding of, for instance, ethics, safety and sustainability. One of the main aspects of the IEP is a strong emphasis on modelling and design, with two compulsory module or classes dedicated to mathematical modelling & analysis for all Faculty of Engineering Sciences programs in Years 1 and 2. The department continues this with another module on computational modelling & analysis in addition to a number of other modules through Years 2-4 (see Table 1). With this approach, the use of computational tools is embedded within the curriculum and within the individual modules. The students learn to solve problems based on traditional approaches, such as McCabe-Thiele diagrams, but also learn how to set up and run Aspen Plus simulations of standard unit operations, and more importantly, how to critically evaluate the results based on the assumptions made in the definition of the problem. As for most UK programs, most modules are compulsory in Years 1-3, and are taken by the entire cohort at the same time. It is therefore possible to properly plan the use of a tool to ensure the material is introduced at the right time and that there is a clear progression from one module to the next or from one year to the next.
2. Integrating computational tools in undergraduate programs The main computational tools used within our program are: MATLAB - for general purpose computation, GAMS - for solving algebraic equation systems and optimization, gPROMS ModelBuilder - for custom modelling of steady-state or dynamic mixed algebraic and differential equations, and Aspen Plus - for process flowsheeting and plant design. Other computational tools are mainly used for research in Year 4 such as ANSYS Fluent and STAR-CCM+ for computational fluid dynamics, and DynoChem scale up for process development. Each tool is introduced in an introductory lecture that outlines the main capabilities of the tool, its usage in the chemical industries and beyond, as well as its basic features. The lecture is followed by one or more tutorials in a large cluster room where the cohort is split into smaller groups from 30 to 70 students. The tutorials are essential to ensure the students are able to first set up a basic problem and then gradually work though a number of problems of increasing complexity. The lecture is given by a dedicated faculty member who has extensive knowledge of each tool. The same person runs the tutorials but now supported by a number of teaching assistants, usually PhD students who are using the tool in their own research.
Use of PSE computational tools across a chemical engineering program
1653
Year 4 (Senior)
Year 3 (Junior)
Year 2 (Sophomore)
Year 1 (Freshman)
Table 1. Chemical engineering program at UCL (modules in grey are based on modeling and make explicit use of computational tools).
Term 1 Engineering Challenges Design & Professional Skills I Mathematical Modelling & Analysis I Introduction to Chemical Engineering Design & Professional Skills II Mathematical Modelling & Analysis II Engineering Experimentation Process Heat Transfer Separation Processes I Process Design Project Process Dynamics & Control Chemical Reaction Engineering II Minor II Research Project Process Systems Engineering & Design Elective Elective
Term 2 Transport Phenomena I Thermodynamics Physical Chemistry Computational Modelling & Analysis Design & Professional Skills II Mathematical Modelling & Analysis II Particulate Systems & Separation Processes II Chemical Reaction Engineering I Minor I Process Design Project Transport Phenomena II Advanced Safety & Loss Prevention Minor III Research Project Elective Elective Elective
Extensive additional resources are available as e-learning resources and cover all the aspects of modelling that the students may encounter in their homework assignments and examinations, for instance, heat exchanger networks, column scheduling, pump sizing etc. The resources are mainly in the form of pdf versions of Powerpoint presentations and are available on the student intranet via Moodle to all students, researchers and staff within the department. Each module also has a dedicated Moodle site, with a dedicated Question & Answer Forum where students can ask questions related to the computational tool or their assignments, and where answers are provided by the teaching faculty to the entire cohort. If additional support is needed, which is very often the case, this is arranged on an as-and-when basis in the form of helpdesk sessions in a smaller computer cluster, again by the same faculty staff. The students can sign up for these via the relevant Moodle site. 2.1. MATLAB MATLAB (Mathworks, 2017) is introduced to all Faculty of Engineering Sciences students in the first compulsory Mathematical Modelling & Analysis module in the first term. The module is taught by a number of academics from across the Faculty, with a weekly 2 hr Faculty lecture followed by a weekly 2 hr tutorial in the home department. The focus is very much on engineering problems, which by their nature can be described by a set of algebraic and/or differential equations. The students learn how to formulate the problems as well as the mathematical concepts required in solving them.
1654
M. Molaei and E.Sorensen
Whilst the lecture presents examples from across all engineering disciplines, the tutorials are based on problems from within the discipline. MATLAB is used for a number of the assignments hence support needs to be available for nearly 800 students. This is provided at Faculty level involving teaching staff, but also a large group of specially trained teaching assistants. The use of MATLAB is continued in the second year in Mathematical Modelling & Analysis II, which runs over the entire academic year with a 2 hr lecture at Faculty level one week and a 2 hr tutorial in the home department the following week. In addition to the compulsory use of MATLAB in these two modules, students may use MATLAB in other assignments throughout their program, for instance in the design of reactors in Chemical Reaction Engineering or for detailed unit design in their capstone Design Project in Year 3. Support is provided by the department in the form of helpdesk sessions for such work but only at the request from students. 2.2. GAMS The first Mathematical Modelling & Analysis module is followed by Computation Modelling & Analysis which is taught in the department and which follows on from the first module by demonstrating how larger systems of equations can be solved by computation tools rather than by hand or using MATLAB. The module is taught in two weekly two hour lectures with tutorials in addition some weeks. GAMS (GAMS, 2017) is introduced first and is used to solve steady-state problems consisting of a number of algebraic equations. The students are given assignments which must be completed as a combination of hand-calculations, Excel spreadsheets and using GAMS. Examples are to solve the mass balances on the form A x = b for a three column systems used to separate benzene, styrene, toluene and xylene, or to maximize the profit for a gas phase reaction system consisting of a mixer, a reactor, two separation units and a recycle stream. As for MATLAB, students may also use GAMS whenever they prefer for other assignments throughout their program. 2.3. gPROMS ModelBuilder The department has used gPROMS (Process Systems Enterprise, 2017) in undergraduate teaching for about 15 years. Until four years ago, gPROMS was only taught in Year 4 as part of our advanced design project. With the introduction of the Integrated Engineering Program (IEP), it was decided to use gPROMS from Year 1 and to cover increasingly complex aspects of the tool term by term and year by year. gPROMS is now introduced in the second part of Computational Modelling & Analysis and is used to solve sets of differential and algebraic systems. Again, the students are given assignments which must be completed as a combination of hand-calculations and using gPROMS. An example is to solve a set of differential equations which describes an aquatic ecosystem and to analyze how pollutants have an impact on water, plants, soil and fish. The use of gPROMS is continued in Year 2, and is incorporated into the two modules considering separation processes. In the first module, students use the tool to investigate the dynamic performance of, for instance, a distillation column stage subject to different disturbances. The students need to simulate and explain the dynamic responses based on their fundamental knowledge of volatility and mass balances for distillation. In the second separation module, students solve a problem related to Acetylsalicylic Acid (ACA) crystallization from Ethanol solution with a continuous MSMPR process. They
Use of PSE computational tools across a chemical engineering program
1655
are free to choose which modelling tool they prefer and many use gPROMS for this instead of MATLAB or GAMS. In Year 3, students consider Process Dynamics and Control, and again use gPROMS to investigate the dynamic behavior of a common unit operation such as a distillation column or a reactor. In Chemical Reaction Engineering, students solve a number of reactor design problems and many use gPROMS for this. The fourth year advanced design project, Process Systems Modelling & Design, builds on the capstone project in Year 3 and considers more advanced design issues such as dynamics, optimization and design under uncertainty. gPROMS is the main tool for this and students consider different design options for a given process, for instance styrene production, and determine the optimal design for both a reaction section and a separation section. They investigate the impact of the main design parameters, such as reactor temperature, scheduling of the distillation columns etc., and they consider the open-loop performance of the plant from both a safety and a production point of view and also propose a suitable control scheme for the overall plant. Some of students will also use gPROMS in their final year research project. gPROMS is the computational tool of choice for the department due to its robust capabilities in simulating large and complex equation systems, but more importantly because it is an easy tool to introduce students to, the learning curve is not too steep and it is easy to introduce the tool in bitesize portions throughout the program. 2.4. ASPEN Plus ASPEN Plus (Aspentech, 2017) is the other main tool used in our program. The students are introduced to the tool in Year 2 and will solve small design problems in each of the two separation modules, e.g. designing a distillation column and consider the impact of tray efficiency on the design. The tool is used extensively in the capstone design project in Year 3, and in the advanced design project in Year 4, for flowsheeting and individual unit design. Some students will also use ASPEN Plus in their research projects. 2.5. Use of computational tools in Scenarios and research-based work In addition to the regular modules and the assignments required for these, students also make extensive use of computational tools in the six week-long scenarios which run throughout Years 1 and 2. The open-ended problem descriptions are generally written in such a way that the students have a choice of which tool to use, which better mirrors the experience they will have as practicing engineers. All Masters’ students will undertake a research project in their final year, and the majority of them will use a computation tool for this. In addition to the main tools mentioned above, they may also make use of tools developed in-house or more advanced tools such as STAR_CCM+ for CFD simulations.
3. e-learning Resources Although all our computational tools are introduced and taught in formal lectures as well as supported by tutorials, extensive e-learning resources are also provided to further support the students as all the nuances and details of a computational tool cannot be conveyed in the form of lectures/tutorials. The e-learning material has been developed mainly in-house and aims to lead the students through different examples and to teach them different aspects of the tools that have not been fully covered during the face-to-face sessions. As an example, for ASPEN Plus we do not cover the detailed use
1656
M. Molaei and E.Sorensen
of all the available unit operations during the lectures/tutorials, but rather we give the students a brief overview in the face-to-face sessions and leave the details to the eleaning material. We update the e-Learning material every year based on what we experience as being difficult for the students, as well as based on direct student feedback. The development of the e-learning material has primarily been done through student summer internships which we have run for three summers with a number of undergraduate students every year. This approach has worked well, as the student interns know better than teaching staff what they themselves found difficult and where more help and support is required.
4. Discussion The use of Process Systems Engineering (PSE) tools across a chemical engineering curriculum may be challenging to deliver in a consistent and meaningful manner across an entire program. First and foremost, faculty that are experienced in the use of the tools is essential, as is teaching assistants with a good working knowledge. Secondly, there is a balance between teaching the tool via lectures and tutorials, based on student selfstudy using e-learning resources and books, or as a combination. There is generally limited time available on the time table to provide in-depth training, and there is often an expectation that tools such as MATLAB or ASPEN Plus are easy to pick up and require little support, however, from a student perspective, these tools are not intuitive and are often a challenge to learn, particularly for weaker students. As a result, the use of PSE computational tools are often not considered as widely as they could, and should, be. Our decision to have a faculty member dedicated to the support of computational tools has not only provided a much better service to our students but has also reduced the workload on colleagues who now receive proper help to formulate their PSE related assignments. One final year student comments: “Across the years I have been at UCL I have been able to see the changes that has been made, and the course has definitely improved. It is particularly noticeable when looking at … and the quality and frequency of programming tutorials.”
5. Conclusion The use of computational tools in a chemical engineering undergraduate program at UCL has been presented. All the main tools are directly embedded into the curriculum and are supported by lectures, tutorials and e-learning resources. This is made possible by a dedicated faculty member who delivers all the training across the program, who works with colleagues in integrating the use of PSE problems and tools, and who supports the students directly in their work.
6. References Aspentech, 2017, http://home.aspentech.com/products/engineering/aspen-plus (viewed Dec 1, 2017) E. Sorensen, 2016, Changing the World – Educating students differently with a more scenario and problem-based engineering curriculum, The Chemical Engineer, 904, 27-31. GAMS, 2017, https://www.gams.com/ (viewed Dec 1, 2017). Process Systems Enterprise, 2017, https://www.psenterprise.com/products/gproms (viewed Dec 1, 2017). Mathworks, 2017, https://www.mathworks.com/products/matlab.html (viewed Dec 1, 2017).