Parallelization Strategies for Efficiently Computing CAD-based Sensitivities for Design Optimization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-disciplinary analysis and optimization (MDAO) has been a long-standing goal in the aerospace community. In order to employ MDAO effectively, one needs to be able to compute the sensitivity of the objective function with respect to the driving parameters in a robust and efficient manner. As models get very large, there is a need to compute these sensitivities in parallel, especially since most optimization methods already employ parallel solvers. Contained herein is a study of two different parallelization strategies for efficiently computing sensitivities. They are compared on a model problem, where the objective is to find the CAD-like design parameters that most-closely match a set of given mass properties. Although quite simple compared with CFD-based optimizations, this model problem allows one to really examine the efficiency and robustness of the parallelization strategies. The results are that for small design changes, a linearized approach to the geometry can be very effective. But for large changes, a non-linear approach, involving rebuilds and computing the sensitivities in parallel with the flow solver, has been found to be the best approach.

Original languageEnglish (US)
Title of host publicationAIAA SciTech Forum 2022
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624106316
DOIs
StatePublished - 2022
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States
Duration: Jan 3 2022Jan 7 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Country/TerritoryUnited States
CitySan Diego
Period1/3/221/7/22

ASJC Scopus subject areas

  • Aerospace Engineering

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