An \(h\)-adaptive RKDG method with troubled-cell indicator for two-dimensional hyperbolic conservation laws
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Publication:380993
DOI10.1007/s10444-012-9287-7zbMath1278.65159OpenAlexW2033965472MaRDI QIDQ380993
Publication date: 15 November 2013
Published in: Advances in Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10444-012-9287-7
Hyperbolic conservation laws (35L65) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65M99)
Related Items (15)
\textit{A posteriori} subcell limiting of the discontinuous Galerkin finite element method for hyperbolic conservation laws ⋮ Approximate Lax-Wendroff discontinuous Galerkin methods for hyperbolic conservation laws ⋮ An \(h\)-adaptive RKDG method for the Vlasov-Poisson system ⋮ Troubled-cell indication using K-means clustering with unified parameters ⋮ An \(h\)-adaptive RKDG method for the two-dimensional incompressible Euler equations and the guiding center Vlasov model ⋮ Theoretical and numerical comparison of hyperelastic and hypoelastic formulations for Eulerian non-linear elastoplasticity ⋮ A hybrid Hermite WENO scheme for hyperbolic conservation laws ⋮ An \(h\)-adaptive RKDG method with troubled-cell indicator for one-dimensional detonation wave simulations ⋮ A Generalization of a Troubled-Cell Indicator to $h$-Adaptive Meshes for Discontinuous Galerkin Methods ⋮ A simple, high-order and compact WENO limiter for RKDG method ⋮ An \(h\)-adaptive local discontinuous Galerkin method for the Navier-Stokes-Korteweg equations ⋮ A New Troubled-Cell Indicator for Discontinuous Galerkin Methods Using K-Means Clustering ⋮ An \(h-\) adaptive local discontinuous Galerkin method for simulating wormhole propagation with Darcy-Forcheiner model ⋮ Shock capturing techniques for \(h p\)-adaptive finite elements ⋮ Three Indication Variables and Their Performance for the Troubled-Cell Indicator using K-Means Clustering
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