Unit information: Advanced Techniques in Multi-Disciplinary Design in 2020/21

Unit name	Advanced Techniques in Multi-Disciplinary Design
Unit code	AENGM2005
Credit points	10
Level of study	M/7
Teaching block(s)	Teaching Block 2 (weeks 13 - 24)
Unit director	Dr. Poole
Open unit status	Not open
Pre-requisites	None
Co-requisites	None
School/department	Department of Aerospace Engineering
Faculty	Faculty of Engineering

Description including Unit Aims

This Unit instructs students in numerical optimisation methods and architectures for executing automated multi-disciplinary sizing of aerospace vehicles. The unit is segmented into four areas of instruction:

1. The design process and requirements for numerical synthesis;

2. Design search and optimisation methods;

3. Advanced multi-disciplinary sub-space simulation and architectures;

4. Design space sensitivities and synthesised solution robustness.

A series of practical examples in conjunction with well-documented case studies will complement the presented material. The coursework emphasises a hands-on approach comprising assignments and a group project.

Intended Learning Outcomes

Upon successful completion of the Unit the student will:

• summarise optimisation methods, including single and multi-objective methods, gradient-based, constraint handling and global methods, and explain the implications of different approaches
• recall definitions of optimisation terminology and explain the conditions for optimality
• select different optimisation approaches for specific problems and defend those choices through appropriate presentation of arguments and data
• develop judicious multi-disciplinary optimisation architectures for solving complex engineering optimisation problems and interpret results through analysis

• present technical data and arguments effectively

Teaching Information

Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.

Assessment Information

100% coursework

Reading and References

• Keane, A.J. & Nair, P.B., Computational Approaches for Aerospace Design: The Pursuit of Excellence. 2005,1st ed., Wiley-Blackwell. ISBN: 0470855401
• Papalambros, P.Y. & Wilde, D.J., Principles of Optimal Design: 'Modeling' & Computation. 2000, 2nd ed., Cambridge University Press. ISBN: 0521622158
• Vanderplaats, G.N., Numerical Optimization Techniques for Engineering Design. 1984, McGraw-Hill. ISBN: 0944956033