Course | Postgraduate |
Semester | Electives |
Subject Code | AE820 |
Subject Title | Multidisciplinary Design Optimization |
Multidisciplinary Design Optimization (MDO): Need and importance – Coupled systems – Anal-yser vs. evaluator – Single vs. bi-level optimisation – Nested vs. simultaneous analysis/design– MDO architectures – Concurrent subspace, collaborative optimisation and BLISS – Sensitivityanalysis – AD (forward and reverse mode) – Complex variable and hyperdual numbers – Gradi-ent and Hessian – Uncertainty quantification – Moment methods – PDF and CDF – Uncertaintypropagation – Monte Carlo methods – Surrogate modelling – Design of experiments – Robust,reliability based and multi-point optimisation formulations
Same as Reference
1. Keane, A. J. and Nair, P. B.,Computational Approaches for Aerospace Design: The Pursuitof Excellence, Wiley (2005).
2. Khuri, A. I. and Cornell, J. A.,Response Surfaces: Design and Analyses, 2nd ed., MarcelDekker (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 Algo-rithmic Differentiation, 2nd ed., SIAM (2008).
5. Forrester, A., Sobester, A., and Keane, A.,Engineering Design via Surrogate Modelling:A Practical Guide, Wiley (2008)