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ArticleFiltered stochastic Galerkin methods for hyperbolic equations

Jonas Kusch2019

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Articlegreen2019

Filtered stochastic Galerkin methods for hyperbolic equations

Jonas Kusch · Ryan G. McClarren · Martin Frank

35 citations·0/0 files stored·Journal of Computational Physics

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Probabilistic and Robust Engineering Design Computational Fluid Dynamics and Aerodynamics Model Reduction and Neural Networks

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References

1991Stochastic Finite Elements: A Spectral Approach 2002Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos 2008Uncertainty quantification for systems of conservation laws 2008Galerkin Method for Wave Equations with Uncertain Coefficients 2013Robust Uncertainty Propagation in Systems of Conservation Laws with the Entropy Closure Method 2009Numerical analysis of the Burgers’ equation in the presence of uncertainty 2018A hyperbolicity-preserving stochastic Galerkin approximation for uncertain hyperbolic systems of equations

Cited by

2022DYNAMICAL LOW-RANK APPROXIMATION FOR BURGERS' EQUATION WITH UNCERTAINTY 2020Intrusive acceleration strategies for uncertainty quantification for hyperbolic systems of conservation laws 2020Spectral convergence of the generalized Polynomial Chaos reduced model obtained from the uncertain linear Boltzmann equation

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Year2019

Typearticle

Published2019-11-01

VenueJournal of Computational Physics

ISSN-L0021-9991

Languageen

Citations35

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.jcp.2019.109073

openalex_workW2887917026

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