A nonlinear data-driven reduced order model for computational homogenization with physics/pattern-guided sampling

DOI10.1016/j.cma.2019.112657zbMath1441.74297OpenAlexW2981114411WikidataQ115063490 ScholiaQ115063490MaRDI QIDQ2175074

Satyaki Bhattacharjee, Karel Matouš

Publication date: 28 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.2019.112657

zbMATH Keywords

parallel computingmachine learningbig datacomputational homogenizationreduced order modelnonlinear manifold

Mathematics Subject Classification ID

Homogenization in equilibrium problems of solid mechanics (74Q05) Applications to the sciences (65Z05) Numerical and other methods in solid mechanics (74S99)

Related Items (1)

Editorial: Special issue on uncertainty quantification, machine learning, and data-driven modeling of biological systems

Uses Software

• Neural Network Toolbox

Cites Work

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