PROCESS MODELLING AND SIMULATION - 2024/5

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

Module Availability

Semester 1

Prerequisites / Co-requisites

Good working knowledge of engineering mathematics is required (including linear algebra, calculus and differential equations).

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:

-          Generic modelling tool - MATLAB, case studies

Assessment pattern

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 in the unseen written examination;

Learning outcomes 2, 3, 4, 5, 6, 7 in Coursework. The coursework involves building process models and solving them numerically using MATLAB.

Thus, the summative assessment for this module consists of:

• Coursework, approx. 20 hours.


• Open-book written examination;

Module aims

• Provide the students with a systematic introduction to the concepts, principles, methods, and related software tools for mathematical modelling and simulation of process systems.

Learning outcomes

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 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 2024/5 academic year.