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A hybrid stochastic Galerkin method for uncertainty quantification applied to a conservation law modelling a clarifier‐thickener unit

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References

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2021B-splines on sparse grids for surrogates in uncertainty quantification19 cited
2022Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification18 cited
2016Computational uncertainty quantification for a clarifier-thickener model with several random perturbations: A hybrid stochastic Galerkin approach17 cited
2015A stochastically and spatially adaptive parallel scheme for uncertain and nonlinear two-phase flow problems15 cited

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2021Multilevel Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data14 cited

2016Stochastic Galerkin framework with locally reduced bases for nonlinear two-phase transport in heterogeneous formations14 cited

2017Intrusive uncertainty quantification for hyperbolic-elliptic systems governing two-phase flow in heterogeneous porous media9 cited

2018Computational uncertainty quantification for some strongly degenerate parabolic convection–diffusion equations8 cited

2014Stochastic Modeling for Heterogeneous Two-Phase Flow7 cited