Probabilistic surrogate models for uncertainty analysis: dimension reduction-based polynomial chaos expansion

DOI10.1002/NME.6262WikidataQ126856225 ScholiaQ126856225MaRDI QIDQ6497714

Yuncheng Du, Jeongeun Son

Publication date: 6 May 2024

Published in: International Journal for Numerical Methods in Engineering (Search for Journal in Brave)

zbMATH Keywords

parametric uncertaintyhigh-dimensional integrationgeneralized polynomial chaosstochastic ordinary differential equationbivariate dimension reduction

Mathematics Subject Classification ID

Stochastic analysis (60Hxx) Numerical methods for partial differential equations, boundary value problems (65Nxx) Probabilistic methods, stochastic differential equations (65Cxx)

Cites Work

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• A gPC-based approach to uncertain transonic aerodynamics
• Uncertainty quantification in control problems for flocking models
• Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos
• Modeling uncertainty in flow simulations via generalized polynomial chaos.
• Efficient Spectral Sparse Grid Methods and Applications to High-Dimensional Elliptic Equations II. Unbounded Domains
• Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation
• Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics
• Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• Efficient Spectral Sparse Grid Methods and Applications to High-Dimensional Elliptic Problems
• High-Order Collocation Methods for Differential Equations with Random Inputs
• A generalized dimension‐reduction method for multidimensional integration in stochastic mechanics

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