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Shape optimization under constraints on the probability of a quadratic functional to exceed a given threshold
Marc Dambrine, Giulio Gargantini, Helmut Harbrecht, Jérôme Maynadier

Shape optimization under constraints on the probability of a quadratic functional to exceed a given threshold

Science & Mathematics Published 2024 Verification Pending

Overview & Synopsis

This article is dedicated to shape optimization of elastic materials under random loadings where the particular focus is on the minimization of failure probabilities. Our approach relies on the fact that the area of integration is an ellipsoid in the high-dimensional parameter space when the shape functional of interest is quadratic. We derive the respective expressions for the shape functional and the related shape gradient. As showcase for the numerical implementation, we assume that the random loading of the state equation under consideration is a Gaussian random field. By exploiting the specialities of this setting, we derive an efficient shape optimization algorithm. Numerical results in three spatial dimensions validate the feasibility of our approach.

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Document Information

Document Title Shape optimization under constraints on the probability of a quadratic functional to exceed a given threshold
Author / Organization Marc Dambrine, Giulio Gargantini, Helmut Harbrecht, Jérôme Maynadier
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-197648
Original Source Link Visit Source Page on hal.science »