Circumventing the solution of inverse problems in mechanics through deep learning: application to elasticity imaging

DOI10.1016/j.cma.2019.04.045zbMath1441.74084OpenAlexW2946534073WikidataQ127875635 ScholiaQ127875635MaRDI QIDQ1988119

Dhruv Patel, Nicholas Hugenberg, Adriana Vega, Li Dong, Assad A. Oberai, Raghav Tibrewala

Publication date: 16 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2019.04.045

zbMATH Keywords

inverse problemsdata augmentationconvolutional neural networkselasticity imagingdomain randomizationphysics based transfer learning

Mathematics Subject Classification ID

Energy minimization in equilibrium problems in solid mechanics (74G65)

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Uses Software

• ImageNet
• AlexNet
• Faster R-CNN

Cites Work

• Unnamed Item
• Solution of the nonlinear elasticity imaging inverse problem: the incompressible case
• Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
• Solution of inverse problems in elasticity imaging using the adjoint method
• Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part II: The Lagrange--Newton Solver and Its Application to Optimal Control of Steady Viscous Flows

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