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Alternate Sampling Methods for use with Multidisciplinary Design Optimization in a High Performance Computing Environment

Authors: Srinivas Kodiyalam and Jaroslaw Sobieszczanski-Sobieski

Abstract

Multidisciplinary Design Optimization (MDO) embodies a set of methodologies which provide a means of coordinating efforts and possibly conflicting recommendations of various disciplinary design teams with well-established analytical tools and expertise. MDO involves multiple disciplines, engineering, business and program management, often with multiple, competing objectives. These disciplines may just be analysis codes, which contain a body of physical principles, or, in addition, they may possess some intelligent decision-making capabilities. In an attempt to address the issues involved with the MDO process, formal methods have been derived, making use of consistent mathematical concepts, unique data structures, and alternative system representation techniques.

Simulation based detailed design of complex systems, more specifically, aerospace and automotive systems, is increasingly becoming a distributed design activity involving multiple decision teams each with very high fidelity models and analysis tools as well as heterogeneous computing environments.

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