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  • 7:17 PM, Tuesday, 22 Sep 2020


Course Postgraduate
Semester Electives
Subject Code AE844
Subject Title Multidisciplinary Design Optimization

Syllabus

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 – Sensitivity analysis – AD (forward and reverse mode) – Complex variable and hyperdual numbers – Gradi- ent 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 Reference

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 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).