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∙ 07/31/2023

A reduced order model for geometrically parameterized two-scale simulations of elasto-plastic microstructures under large deformations

In recent years, there has been a growing interest in understanding comp...

0 Theron Guo, et al. ∙

∙ 01/27/2023

A Greedy Sensor Selection Algorithm for Hyperparameterized Linear Bayesian Inverse Problems

We consider optimal sensor placement for a family of linear Bayesian inv...

0 Nicole Aretz, et al. ∙

∙ 10/05/2022

A Reduced Basis Ensemble Kalman Method

In the process of reproducing the state dynamics of parameter dependent ...

0 Francesco A. B. Silva, et al. ∙

∙ 06/27/2022

Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: Extension to geometrical parameterizations

Understanding structure-property relations is essential to optimally des...

0 Theron Guo, et al. ∙

∙ 01/25/2022

Multiscale modeling of linear elastic heterogeneous structures based on a localized model order reduction approach

In analyzing large scale structures it is necessary to take into account...

0 Philipp Diercks, et al. ∙

∙ 04/09/2021

Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method

In order to optimally design materials, it is crucial to understand the ...

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∙ 11/23/2020

A sequential sensor selection strategy for hyper-parameterized linear Bayesian inverse problems

We consider optimal sensor placement for hyper-parameterized linear Baye...

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