Numerical upscaling of parametric microstructures in a possibilistic uncertainty framework with tensor trains
DOI10.1007/s00466-022-02261-zOpenAlexW4313256501MaRDI QIDQ2692897
Dieter Moser, Martin Eigel, Robert Gruhlke, Lars Grasedyck
Publication date: 17 March 2023
Published in: Computational Mechanics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00466-022-02261-z
linear elasticitypossibilityfuzzy partial differential equationsuncertainty quantificationhomogenisationlow-rank tensor formatsparametric partial differential equationstensor trainspolymorphic uncertainty modeling
Classical linear elasticity (74B05) Stability and convergence of numerical methods for boundary value problems involving PDEs (65N12) Numerical solutions to equations with linear operators (65J10) Multilinear algebra, tensor calculus (15A69) Mechanics of deformable solids (74-XX) Numerical solution of discretized equations for boundary value problems involving PDEs (65N22) Fuzzy partial differential equations (35R13) Interpolation and approximation (educational aspects) (97N50)
Uses Software
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