Abstract

This paper deals with the convergence of the second-order GRP(Generalized Riemann Problem) numerical scheme to the entropysolution for scalar conservation laws with strictly convex fluxes.The approximate profiles at each time step are linear in each cell,with possible jump discontinuities (of functional values and slopes)across cell boundaries. The basic observation is that the discretevalues produced by the scheme are exact averages of an approximate conservation law, which enables the use of propertiesof such solutions in the proof. In particular, the“total-variation" of the scheme can be controlled, using analyticproperties. In practice, the GRP code allows “sawteeth" profiles(i.e., the piecewise linear approximation is not monotone even ifthe sequences of averages is such). The “reconstruction" procedureconsidered here also allows the formation of “sawteeth" profiles,with an hypothesis of “Godunov Compatibility", which limits theslopes in cases of non-monotone profiles. The scheme is proved toconverge to a weak solution of the conservation law. In the case ofa monotone initial profile it is shown (under a further hypothesison the slopes) that the limit solution is indeed the entropysolution. The constructed solution satisfies the “finitepropagation speed", so that no rarefaction shocks can appear inintervals such that the initial function is monotone in their domainof dependence. However, the characterization of the limit solutionas the unique entropy solution, for general initial data, is stillan open problem.

Highlights

  • In this paper we study the convergence of high resolution second order numerical schemes to entropy solutions of the initial value problem for scalar conservation laws

  • We introduce the concept of “monotone chains” and establish the relation between the exact solution of the approximate equation and the discrete GRP scheme. It leads to the necessary bounds on the total variation, which enable us to prove in Section 5 the convergence of the discrete scheme to a weak solution (of (1))

  • Note that the equalities inf x vn(x) inf j vjn and sup vn(x) sup vjn j follow from the construction of {snj }∞ j=−∞ in the preceding section. As another interesting feature of the GRP scheme, we derive from Proposition 3.8 the property that at a local maximum the approximate solution vn(x) cannot increase

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Summary

Introduction

We do not exclude this possibility, but impose certain hypotheses (see details at the end of Section 2 below) that (a) ensure that the total-variation remains bounded, namely, that the scheme is TVB and converges to a weak solution of (1) by compactness and (b) limit the number of “large slopes” and ensure that (in the case of monotone initial profiles) the limit solution satisfies all the entropy conditions. It leads to the necessary bounds on the total variation, which enable us to prove in Section 5 the convergence of the discrete scheme to a weak solution (of (1)).

The and value of
It was shown that
Assume first
We prove for j
If the shock at
In view
We now estimate the difference
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