Negative-order norm estimates for nonlinear hyperbolic conservation laws

Liangyue Ji, Yan Xu, Jennifer K. Ryan

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


In this paper, we establish negative-order norm estimates for the accuracy of discontinuous Galerkin (DG) approximations to scalar nonlinear hyperbolic equations with smooth solutions. For these special solutions, we are able to extract this "hidden accuracy" through the use of a convolution kernel that is composed of a linear combination of B-splines. Previous investigations into extracting the superconvergence of DG methods using a convolution kernel have focused on linear hyperbolic equations. However, we now demonstrate that it is possible to extend the Smoothness-Increasing Accuracy-Conserving filter for scalar nonlinear hyperbolic equations. Furthermore, we provide theoretical error estimates for the DG solutions that show improvement to (2κ +m)-th order in the negative-order norm, where m depends upon the chosen flux.

Original languageEnglish (US)
Pages (from-to)531-548
Number of pages18
JournalJournal of Scientific Computing
Issue number2-3
StatePublished - Feb 1 2013


  • Discontinuous galerkin method
  • Negative-order norm
  • Nonlinear hyperbolic conservation laws
  • Post-processing
  • SIAC filtering

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