An adaptive domain-based POD/ECM hyper-reduced modeling framework without offline training

An adaptive domain-based POD/ECM hyper-reduced modeling framework without offline training

Rocha, I.B.C.M. (TU Delft Applied Mechanics)
van der Meer, F.P. (TU Delft Applied Mechanics)
Sluys, Lambertus J. (TU Delft Materials- Mechanics- Management & Design)

Materials- Mechanics- Management & Design

2020

This work presents a reduced-order modeling framework that precludes the need for offline training and adaptively adjusts its lower-order solution space as the analysis progresses. The analysis starts with a fully-solved step and elements are clustered based on their strain response. Elements with the highest strains are solved with a local/global approach in which degrees of freedom from elements undergoing the highest amount of nonlinearity are fully-solved and the rest is approximated by a Proper Orthogonal Decomposition (POD) reduced model with full integration. Elements belonging to the remaining clusters are subjected to a hyper-reduction step using the Empirical Cubature Method (ECM). Online error estimators are used to trigger a retraining process once the reduced solution space becomes inadequate. The performance of the framework is assessed through a series of numerical examples featuring a material model with pressure-dependent plasticity.

Adaptive reduction
Hyper-reduction
Local/global approach
Reduced-order modeling

http://resolver.tudelft.nl/uuid:cd217897-0594-4fe7-80ee-15d7daa212c5

https://doi.org/10.1016/j.cma.2019.112650

0045-7825

Computer Methods in Applied Mechanics and Engineering, 358

Institutional Repository

journal article

© 2020 I.B.C.M. Rocha, F.P. van der Meer, Lambertus J. Sluys