High-Dimensional Uncertainty Quantification in a Hybrid Data + Model-Based Submodeling Method for Refined Response Estimation at Critical Locations
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 3
Abstract
This study presents frameworks to build nonintrusive polynomial chaos expansion (PCE) models with regression and Smolyak sparse-grid quadrature to perform high-dimensional uncertainty propagation and uncertainty quantification (UQ) for response estimated with the hybrid data + model-based submodeling (HDMS) method. The HDMS method drives the finite-element submodel containing a critical location of a structure using the measured response of the real structure at the preselected submodel boundaries to estimate a refined response distribution around the critical location. The proposed UQ frameworks are implemented on an experimental case study of a plate with holes as critical locations under tensile loading. The UQ results at the critical locations from regression-based PCE models built using different sampling methods and the Smolyak sparse-grid quadrature-based PCE models are compared with the UQ results from the traditional Monte Carlo simulation (MCS) method. The regression-based PCE model with Smolyak sparse-grid sampling demonstrated significantly higher accuracy in distribution parameters and probability density functions (pdf) compared to the other regression-based PCE models. While the Smolyak quadrature-based PCE model with a considerably small experimental design showed slightly lower accuracy, it still outperforms regression-based PCE models with MC-based sampling.
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Data Availability Statement
Some data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, which includes the DIC data, finite-element submodel of the plate, and the code defining the loads at each boundary.
Acknowledgments
Research funding is partially provided by the National Science Foundation through Grant No. CMMI-1351537, by the Hazard Mitigation and Structural Engineering program, and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA). Author B.V. would like to thank J. Saunders and Y. Chen of Lehigh University for their help with data collection in the case study of the plate with holes.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 3 • September 2021
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© 2021 American Society of Civil Engineers.
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Received: Jul 15, 2020
Accepted: Feb 24, 2021
Published online: May 20, 2021
Published in print: Sep 1, 2021
Discussion open until: Oct 20, 2021
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