Conditional stochastic simulations of flow and transport with Karhunen-Loève expansions, stochastic collocation, and sequential Gaussian simulation

DOI10.1155/2014/652594zbMath1442.76091OpenAlexW2105845830WikidataQ59053945 ScholiaQ59053945MaRDI QIDQ2336619

Mina Ossiander, Veronika S. Vasylkivska, Małgorzata Peszyńska

Publication date: 19 November 2019

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/652594

Mathematics Subject Classification ID

Stochastic analysis applied to problems in fluid mechanics (76M35) Stability and convergence of numerical methods for boundary value problems involving PDEs (65N12) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30)

Related Items (4)

Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models ⋮ Physics-informed Karhunen-Loéve and neural network approximations for solving inverse differential equation problems ⋮ Hybrid three-scale model for evolving pore-scale geometries ⋮ Gaussian process regression and conditional polynomial chaos for parameter estimation

Uses Software

• GSLIB
• IPARS

Cites Work

• Kernel principal component analysis for efficient, differentiable parametrization of multipoint geostatistics
• Stochastic collocation and mixed finite elements for flow in porous media
• The multivariate normal distribution
• An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loève and polynomial expansions.
• Probabilistic characterization of transport in heterogeneous media
• Modeling groundwater flow and contaminant transport
• Godunov-Mixed Methods for Advection-Diffusion Equations in Multidimensions
• Theoretical Numerical Analysis
• A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
• An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
• Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients
• Mixed and Hybrid Finite Element Methods
• A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data
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