PROCESS MODELLING AND SIMULATION - 2023/4
Module code: ENGM214
Module Overview
This module provides students with a systematic framework of building, solving and applying mathematical models of process systems in a variety of contexts related to chemical engineering and the wider engineering disciplines. Students will acquire the knowledge of the main concepts, methods, and tools of process modelling and simulation, including state-of-the-art process simulation software. Apart from teaching the methods of mathematical modelling, the module develops general problem-solving and algorithmic skills applicable in many areas of employment.
Module provider
Chemistry and Chemical Engineering
Module Leader
KLYMENKO Oleksiy (Chst Chm Eng)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 84
Lecture Hours: 11
Tutorial Hours: 22
Guided Learning: 22
Captured Content: 11
Module Availability
Semester 1
Prerequisites / Co-requisites
None.
Module content
Indicative content includes:
1. General concepts: System, model, simulation.
2. Construction of mechanistic models: conservation laws, constitutive relations, dynamic and steady-state models, lumped and distributed models.
3. Solution of equation systems (simulation): algebraic equation systems, differential/ algebraic differential equation systems, partial differential systems.
4. Parameter estimation: data acquisition, parameter estimation methods, error analysis.
5. Modular simulation: sequential approach, partitioning, convergence of loops, simultaneous modular approach.
6. Introduction to data-driven/statistical modelling: regression models, artificial neural networks, hybrid models.
7. Introduction to modelling and simulation tools:
- Flowsheeting tool – ASPEN Plus, case studies
- Generic modelling tool - MATLAB, case studies
Assessment pattern
Assessment type | Unit of assessment | Weighting |
---|---|---|
Coursework | COURSEWORK | 25 |
Examination | 2hr Invigilated Exam | 75 |
Alternative Assessment
N/A
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate
Learning outcomes 1, 2, 3, 4 on the unseen written examination;
Learning outcomes 2, 3, 4, a, b, c on Coursework; The coursework will involve simulation of the various types of unit operations present in a process flowsheet, using ASPEN Plus.
Thus, the summative assessment for this module consists of:
- Coursework, approx. 20 hours.
- Open-book written examination;
Formative assessment and feedback
The students will receive feedback on their learning, in-class tutorial, problems and coursework. Formative assessment will also be carried out on problem solving using Matlab.
Module aims
- Provide the students with a systematic introduction to the concepts, principles, methods, and related software tools for mathematical modelling and simulation of chemical process systems.
Learning outcomes
Attributes Developed | ||
001 | Identify and explain the types of mathematical models | KC |
002 | Explain and apply the workflow of developing models and conducting numerical simulations | P |
003 | Select the proper type of methods and tools for a given problem ; | KPT |
004 | Apply standard tools to solve practical engineering problems | PT |
005 | Working independently and with initiative; | T |
006 | Finding and assessing information; | T |
007 | Managing time and working to deadlines. | T |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
Guide the student through modelling from unit to production level concluding the learning process with flowsheet simulation.
The learning and teaching methods include:
- captured content
- lectures
- tutorials
- supervised computer labs
- independent learning
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ENGM214
Other information
This module contributes to the student development in the following ways aligned with the five pillars of the Surrey Curriculum Framework:
Digital capabilities: this module develops programming skills using MATLAB and exposes students to state-of-the-art process simulation software (Aspen Plus) which is widely used in industry. Students will be developing their general IT skills by engaging with SurreyLearn and other electronic resources provided to them.
Employability: the knowledge and skills in mathematical modelling and numerical simulation acquired in this module are applicable to a wide range of situations in engineering and beyond. The module equips students not only with tools they can use to develop mechanistic and data-driven models of various processes but also with a systematic approach to problem-solving and systems analysis skills.
Resourcefulness and resilience: tutorial problems, computer labs and coursework assignment require students to put considerable effort into solving challenging problems to develop their reasoning and problem-solving skills. This enhances students’ resilience and resourcefulness.
Sustainability: systematic process modelling is key to quantitative understanding of system behaviour which minimises the need in experimentation, likelihood of failures and provides means for rigorous optimisation of system performance, including measures of efficiency and sustainability. Thus, this module has sustainability at its core since the systematic modelling leads to the development of ‘greener’ industrial processes.
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.