Design Optimisation and Simulation (894H1)
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Design Optimisation and Simulation
Module 894H1
Module details for 2024/25.
15 credits
FHEQ Level 7 (Masters)
Module Outline
In this module you will develop a systematic understanding of optimisation, identifying the appropriate
categories and numerical solution methods for a range of canonical, and industry, engineering design
problems. You will be introduced to a range of advanced optimisation techniques and develop an
awareness of the emergent techniques. Practical implementation of optimisation will be via
development of your skills in advanced finite element analysis, moving towards APDL scripting
enabling you to automate repetitive GUI based tasks in design studies. Drawing on the much wider
field of operation research, you will develop skills in discrete-event simulation, using Mathworks
SimEvents to model complex manufacturing processes and inform critical decision making in resourceconstrained
industrial environment.
Indicative Content (CC indicates Core Curriculum content)
• Introduction to engineering design optimisation
• Overview of numerical methods and solvers, including Newton-based methods for non-linear
problems.
• Gradient based optimisation in constrained and unconstrained problems
• Discrete and gradient free optimisation
• Multi-objective optimisation
• Advanced optimisation concepts: surrogate and deep learning models, genetic and
evolutionary algorithms
o CC: English and Maths
• Contact modelling and analysis.
• Buckling modelling and analysis (column, shear, flexural)
• Thermo-structural modelling and analysis.
Module learning outcomes
Understand advanced techniques for Finite Element Analysis modelling and
automate design studies using ANSYS APDL scripting.
Assess unfamiliar structural and thermal systems critically, and draw conclusions
for optimal practical and manufacturable solutions in complex problems.
Comprehensively identify key aspects of engineering design optimisation and
apply appropriate solution methods to a range of problem classes.
Develop new optimised manufacturing processes and their industry-relevant
authorisation workflows using discrete event simulation methodologies.
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 100.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | VACATION Week 4 | 50.00% |
| Report | A3 Week 1 | 50.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Summer Teaching | Lecture | 1 hour | 501 |
| Summer Teaching | Laboratory | 2 hours | 211 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Chang Wang
Assess convenor
/profiles/328884
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