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2023/24 Taught Postgraduate Module Catalogue
CIVE5024M Design Optimisation - MEng
15 creditsClass Size: 45
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
The pre-requisite modules given are for students following programmes in MEng, BEng Aeronautical and Aerospace Engineering, and MEng, BEng Mechanical EngineeringPre-requisites
| MECH1220 | Computers in Engineering Analysis |
| MECH1230 | Solid Mechanics |
| MECH1520 | Engineering Mathematics |
| MECH2610 | Engineering Mechanics |
| MECH3900 | Finite Element Methods of Analysis |
This module is mutually exclusive with
| CIVE5971M | Design Optimisation - MSc |
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 websiteLast updated: 28/04/2023 14:52:55
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