Uncertainty quantification for a 1D thermo-hyperelastic coupled problem using polynomial chaos projection and \(p\)-FEMs

DOI10.1016/j.camwa.2015.04.024zbMath1443.65377OpenAlexW328558596MaRDI QIDQ2006464

Danny Weiss, Zohar Yosibash

Publication date: 11 October 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2015.04.024

zbMATH Keywords

polynomial chaosthermo-hyperelasticity\(p\)-FEcoupled-problems

Mathematics Subject Classification ID

Probabilistic methods, particle methods, etc. for boundary value problems involving PDEs (65N75) Nonlinear elasticity (74B20) Thermal effects in solid mechanics (74F05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45)

Related Items (1)

Error Estimation of Polynomial Chaos Approximations in Transient Structural Dynamics

Uses Software

• nwSpGr
• PATSYM

Cites Work

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• Likelihood approximation by numerical integration on sparse grids
• High-order FEMs for thermo-hyperelasticity at finite strains
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• Multi-level Monte Carlo finite element method for elliptic PDEs with stochastic coefficients
• Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations
• Sparse polynomial chaos expansions and adaptive stochastic finite elements using a regression approach
• Stochastic modeling of coupled electromechanical interaction for uncertainty quantification in electrostatically actuated MEMS
• Stochastic simulation of riser-sections with uncertain measured pressure loads and/or uncertain material properties
• Polynomial normal densities generated by Hermite polynomials
• Fully symmetric interpolatory rules for multiple integrals over infinite regions with Gaussian weight
• Dimension reduction in stochastic modeling of coupled problems
• Spectral Methods for Uncertainty Quantification
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• Sparse grids

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