PROCESS MODELLING AND SIMULATION - 2022/3
Module code: ENGM214
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
This module addresses the concepts, methods, and tools of process modelling and simulation.
Chemical and Process Engineering
KLYMENKO Oleksiy (Chm Proc Eng)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: G150
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 95
Lecture Hours: 11
Tutorial Hours: 11
Guided Learning: 22
Captured Content: 11
Prerequisites / Co-requisites
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 type||Unit of assessment||Weighting|
|Examination Online||ONLINE (OPEN BOOK) EXAM||75|
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:
- Unseen written examination, 2 hours;
- Coursework, approx. 20 hours.
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.
- Provide a systematic introduction to the concepts, principles, methods, and related software tools for mathematical modelling and simulation of chemical process systems.
|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|
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:
22 hours of lectures in 11 weeks
11 hours of supervised computer supervised computer labs in 11 weeks
Reviewing lecture: 2 hours Week 12
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.
Upon accessing the reading list, please search for the module using the module code: ENGM214
Programmes this module appears in
|Chemical Engineering MEng||1||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Chemical and Petroleum Engineering MEng||1||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Process Systems Engineering MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Renewable Energy Systems Engineering MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Petroleum Refining Systems Engineering MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Information and Process Systems Engineering MSc||1||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
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 2022/3 academic year.