• Mathematics, Computer Science
  • Published in
    Multiscale Modeling…
    2017
  • DOI:10.1137/17M1151730

Hypocoercivity Based Sensitivity Analysis and Spectral Convergence of the Stochastic Galerkin Approximation to Collisional Kinetic Equations with Multiple Scales and Random Inputs

@article{Liu2017HypocoercivityBS,
  title={Hypocoercivity Based Sensitivity Analysis and Spectral Convergence of the Stochastic Galerkin Approximation to Collisional Kinetic Equations with Multiple Scales and Random Inputs},
  author={Liu Liu and Shi Jin},
  journal={Multiscale Modeling & Simulation},
  year={2017},
  volume={16},
  pages={1085-1114}
}
In this paper, we provide a general framework to study general class of linear and nonlinear kinetic equations with random uncertainties from the initial data or collision kernels, and their stochastic Galerkin approximations, in both incompressible Navier-Stokes and Euler (acoustic) regimes. First, we show that the general framework put forth in [C. Mouhot and L. Neumann, Nonlinearity, 19, 969-998, 2006, M. Briant, J. Diff. Eqn., 259, 6072-6141, 2005] based on hypocoercivity for the… CONTINUE READING

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