Learning nonlinear constitutive models in finite strain electromechanics with Gaussian process predictors

DOI10.1007/s00466-024-02446-8MaRDI QIDQ6630898

Rogelio Ortigosa, Nathan Ellmer, Jesús Martínez-Frutos, A. Pérez-Escolar, Antonio J. Gil

Publication date: 31 October 2024

Published in: Computational Mechanics (Search for Journal in Brave)

zbMATH Keywords

krigingmachine learningelectromechanicsconstitutive modellingelectro active polymers

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX)

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