Bilevel Data-Driven Modeling Framework for High-Dimensional Structural Optimization under Uncertainty Problems
This article has been corrected.
VIEW CORRECTIONPublication: Journal of Structural Engineering
Volume 146, Issue 11
Abstract
Optimization under uncertainty (OUU) is a robust framework to obtain optimal designs for real engineering problems considering uncertainties. The numerical solution for large-scale problems involving millions of degrees-of-freedom is typically computation-intensive in nature. Also, OUU problems constitutes an uncertainty analysis, involving a computation-intensive numerical solver for large-scale systems. Hence, the solution of OUU problems are computationally demanding in nature. In this study, a bilevel data-driven modeling framework is proposed using proper orthogonal decomposition (POD) and polynomial chaos expansion (PCE) metamodels. A heuristic particle swarm optimization (PSO) technique is used for optimization. The effectiveness of the POD-PCE metamodel combined with PSO is demonstrated for two practical large-scale structural optimizations under uncertainty problems. From the case studies, it has been observed that the proposed method gives solutions that are almost hundreds and thousands of times faster as compared to the crude Monte Carlo simulation.
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Data Availability Statement
All data generated or analyzed during the study are available as “Supplemental Materials” along with the manuscript. Some or all data, models, or code generated or used during the study are available from the authors by request.
Acknowledgments
We would like to sincerely thank the anonymous reviewers, whose constructive comments have significantly enhanced the quality of this manuscript. We also highly appreciate the help provided by Mr. Aniket Kumar, Master’s Student in the Department of Civil Engineering, National Institute of Technology Silchar, for the result extraction for the optimization of the 244-member tower.
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Published In
Journal of Structural Engineering
Volume 146 • Issue 11 • November 2020
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© 2020 American Society of Civil Engineers.
History
Received: Jul 28, 2019
Accepted: May 11, 2020
Published online: Aug 24, 2020
Published in print: Nov 1, 2020
Discussion open until: Jan 24, 2021
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