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• W2792138812 abstract "Kinetic equations contain uncertainties in their collision kernels or scattering coefficients, initial or boundary data, forcing terms, geometry, etc. Quantifying the uncertainties in kinetic models have important engineering and industrial applications. In this article we survey recent efforts in the study of kinetic equations with random inputs, including their mathematical properties such as regularity and long-time behavior in the random space, construction of efficient stochastic Galerkin methods, and handling of multiple scales by stochastic asymptotic-preserving schemes. The examples used to illustrate the main ideas include the random linear and nonlinear Boltzmann equations, linear transport equation and the Vlasov-Poisson-Fokker-Planck equations." @default.
• W2792138812 created "2018-03-29" @default.
• W2792138812 creator A5017812804 @default.
• W2792138812 creator A5019581016 @default.
• W2792138812 date "2017-01-01" @default.
• W2792138812 modified "2023-09-23" @default.
• W2792138812 title "Uncertainty Quantification for Kinetic Equations" @default.
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• W2792138812 doi "https://doi.org/10.1007/978-3-319-67110-9_6" @default.
• W2792138812 hasPublicationYear "2017" @default.
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