$ x $ | 0.1850 | 0.1855 | 0.1860 | 0.1865 | 0.1870 | 0.1875 | 0.1880 | 0.1885 |
Godunov | 0.9999 | 0.9991 | 0.9936 | 0.9580 | 0.7647 | 0.2724 | 0.0123 | 0.0000 |
GMP | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.0000 | 0.0000 | 0.0000 |
We propose to solve hyperbolic partial differential equations (PDEs) with polynomial flux using a convex optimization strategy.This approach is based on a very weak notion of solution of the nonlinear equation,namely the measure-valued (mv) solution,satisfying a linear equation in the space of Borel measures.The aim of this paper is,first,to provide the conditions that ensure the equivalence between the two formulations and,second,to introduce a method which approximates the infinite-dimensional linear problem by a hierarchy of convex,finite-dimensional,semidefinite programming problems.This result is then illustrated on the celebrated Burgers equation.We also compare our results with an existing numerical scheme,namely the Godunov scheme.
Citation: |
Table 1.
Approximation of
$ x $ | 0.1850 | 0.1855 | 0.1860 | 0.1865 | 0.1870 | 0.1875 | 0.1880 | 0.1885 |
Godunov | 0.9999 | 0.9991 | 0.9936 | 0.9580 | 0.7647 | 0.2724 | 0.0123 | 0.0000 |
GMP | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 0.0000 | 0.0000 | 0.0000 |
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Approximation of the solution
Approximation of the solution