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  • 12:07 AM, Wednesday, 20 Nov 2019


Course Undergraduate
Semester Electives
Subject Code AE496
Subject Title Multidisciplinary Design Optimization

Syllabus

Multidisciplinary Design Optimization (MDO) – need and importance, coupled systems – analyser vs. evaluator, single vs. bi-level optimisation, nested vs. simultaneous analysis/design MDO architectures – concurrent subspace, collaborative optimisation and BLISS – sensitivity analysis, AD (forward and reverse mode), complex variable, and hyperdual numbers – gradient and Hessian – uncertainty quantification – moment methods – PDF and CDF – uncertainty propagation – Monte Carlo methods – surrogate modelling – design of experiments – robust, reliability based and multi-point optimisation formulations.

Text Books

Same as References

References

1. Keane, A. J. and Nair, P. B., Computational Approaches for Aerospace Design: The Pursuit of Excellence, Wiley (2005).

2. Khuri, A. I. and Cornell, J. A., Response Surfaces: Design and Analyses, 2nd ed., Marcel Dekker (1996).

3. Montgomery, D. C., Design and Analysis of Experiments, 8th ed., John Wiley (2012).

4. Griewank, A. and Walther, A., Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, 2nd ed., SIAM (2008).