Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: application to planar soft tissues

DOI10.1016/j.cma.2022.115812OpenAlexW4310968331WikidataQ125847651 ScholiaQ125847651MaRDI QIDQ2678528

Bjørn Sand Jensen, Sanjay Pant, Chung-Hao Lee, Ankush Aggarwal

Publication date: 23 January 2023

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

Full work available at URL: https://arxiv.org/abs/2210.00868

zbMATH Keywords

Gaussian processesnonlinear elasticitymachine learningstochastic finite element analysisconstitutive modelingtissue biomechanics

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Biology and other natural sciences (92-XX)

Related Items (2)

Gradient enhanced Gaussian process regression for constitutive modelling in finite strain hyperelasticity ⋮ Dual order-reduced Gaussian process emulators (DORGP) for quantifying high-dimensional uncertain crack growth using limited and noisy data

Uses Software

• FEBio
• Bayesian-EUCLID

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