Stochastic Solvers for the Euler Equations
نویسنده
چکیده
In this paper we extend our previous work, first presented in, to handle effectively non-Gaussian processes and long-time integration in unsteady simulations of compressible flows. Specifically, we apply the generalized polynomial chaos (GPC) method to solve the one-dimensional stochastic Euler equations. We present systematic verification studies against an analytical solution of the stochastic piston problem for different correlation lengths of the time-dependent random piston motion, which may follow a Gaussian or a uniform distribution. A new multi-element decomposition of the random space is presented that provides more robustness and resolution capability, and comparisons are made against Monte Carlo simulations.
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