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Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model ApproachThis work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.
Document ID
20170006496
Acquisition Source
Langley Research Center
Document Type
Conference Paper
Authors
Aguilo, Miguel A.
(Sandia National Labs. Albuquerque, NM, United States)
Warner, James E.
(NASA Langley Research Center Hampton, VA, United States)
Date Acquired
July 12, 2017
Publication Date
June 4, 2017
Subject Category
Metals And Metallic Materials
Report/Patent Number
NF1676L-27189
Meeting Information
Meeting: Engineering Mechanics Institute Conference (EMI 2017)
Location: San Diego, CA
Country: United States
Start Date: June 4, 2017
End Date: June 7, 2017
Sponsors: San Diego Univ.
Funding Number(s)
CONTRACT_GRANT: DE-AC04-94AL85000
WBS: WBS 533127.02.16.07.06
Distribution Limits
Public
Copyright
Public Use Permitted.
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