# 2023/24 Taught Postgraduate Module Catalogue

## CIVE5971M Design Optimisation - MSc

### 15 creditsClass Size: 90

Module manager: Professor Harvey Thompson
Email: H.M.Thompson@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2023/24

### Pre-requisite qualifications

BEng degree with at least 2:1 honours and must have studied Finite Element Analysis module in undergraduate degree.

### This module is mutually exclusive with

 CIVE5024M Design Optimisation - MEng

This module is not approved as an Elective

### Objectives

On completion of this module students should acquire a comprehensive understanding of the scientific principles of design optimisation and ability to arrive at an improved design for an engineering system that satisfies given requirements.
Having completed the module students should be able to: formulate a design optimisation problem that is treated as a systematic design improvement; select, compare, contrast, understand limitations and apply appropriate methods and computer software for solving such problems; critically interpret the obtained results. The emphasis is made on the application of modern optimisation techniques linked to the numerical methods of analysis of engineering systems.

Skills outcomes
General learning outcomes (UK-SPEC): the ability to apply new concepts and methods (in the context of design optimisation as systematic design improvement).
Specific learning outcomes (UK-SPEC): Underpinning Science & Mathematics (Knowledge and understanding of mathematical methods as applied to design optimisation; an appreciation of the limits of such methods); Engineering Analysis (the ability to apply mathematical methods to solve problems in design optimisation; the ability to assess the advantages and limitations of particular cases); Design (broader knowledge and understanding of design improvement aims and techniques for a chosen engineering system); Engineering Practice (a thorough understanding of how simulation-based optimisation techniques influence design methods and engineering practice).

### Syllabus

1. Introduction to the course, motivation for the systematic design improvement. Criteria of design quality. Formulation of an optimization problem as a nonlinear mathematical programming problem. Choice of design variables and the objective function. Formulation of typical constraints on the system's behaviour.
2. Classification of design optimization problems. Constrained and unconstrained problems. Global and local optima. Kuhn-Tucker optimality conditions. Multi-objective problems. Pareto optimum solutions. Basic approaches to the formulation of a combined criterion.
3. Numerical optimization techniques. Local and global one-dimensional optimization. Unconstrained multi-parameter optimization techniques. Penalty methods. Linear programming. General constrained optimization techniques. Random search, genetic algorithms.
4. Approximation techniques. Local, mid-range and global approximations, used in conjunction with a high fidelity numerical analysis. Design of Experiments (DoE) techniques for sampling in approximation building. Case studies and applications to practical problems.
5. Design sensitivity analysis based on the finite element modelling of structural behaviour. Analytical, semi-analytical, and finite difference techniques.
6. The relationships between fully-stressed and minimum weight structures. Topology, shape and sizing optimization. Case studies and applications to practical problems.
7. Other applications of optimization techniques in engineering. Structural identification problems: finite element model identification, material parameter identification, structural damage recognition.
8. Effect of stochastic inputs on an engineering system, stochastic analysis optimization, robust design, reliability optimization.
9. Real-life examples of design optimization. Review of availability of commercial software.

### Teaching methods

 Delivery type Number Length hours Student hours Lecture 22 1.00 24.00 Tutorial 11 1.00 9.00 Private study hours 117.00 Total Contact hours 33.00 Total hours (100hr per 10 credits) 150.00

### Private study

22 hours revision for lectures, 22 hours (2 hours per tutorial) for preparation & revision for tutorials, 25 hours for preparation for assessment, 50 hours for preparation for examination.

Topics of directed independent study identified by lecturer to support learning. Such topics will include applications of design optimisation techniques to structural design, study of specialist technical reports and relevant journal papers (e.g. Structural and Multidisciplinary Optimization, ICE Proceedings, ASCE Journal of Structural Engineering, AIAA Journal).
Non-assessed tutorial questions covering structural topology and shape optimisation and approximation-based optimisation.

### Opportunities for Formative Feedback

Progress will be monitored in the tutorial periods.

### Methods of assessment

Coursework
 Assessment type Notes % of formal assessment Assignment Design Problems 30.00 Total percentage (Assessment Coursework) 30.00

The resit will be by online time-limited assessment only.

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 3 hr 00 mins 70.00 Total percentage (Assessment Exams) 70.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

### Reading list

The reading list is available from the Library website

Last updated: 28/04/2023 14:52:56

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