Numerical approximation of statistical solutions of scalar conservation laws
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2017-10
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Report
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Abstract
We propose efficient numerical algorithms for approximating statistical solutions of scalar conservation laws. The proposed algorithms combine finite volume spatio-temporal approximations with Monte Carlo and multi-level Monte Carlo discretizations of the probability space. Both sets of methods are proved to converge to the entropy statistical solution. We also prove that there is a considerable gain in efficiency resulting from the multi-level Monte Carlo method over the standard Monte Carlo method. Numerical experiments illustrating the ability of both methods to accurately compute multi-point statistical quantities of interest are also presented.
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published
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2017-52
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Seminar for Applied Mathematics, ETH Zurich
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03851 - Mishra, Siddhartha / Mishra, Siddhartha
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306279 - Structure preserving approximations for robust computation of conservation laws and related equations (EC)