Multi-dimensional Optimal Order Detection (MOOD) — A very high-order Finite Volume Scheme for conservation laws on unstructured meshes.

Steven Diot (1) , Stéphane Clain (1) , Raphaël Loubère (1)

1 IMT - Institut de Mathématiques de Toulouse UMR5219

The Multi-dimensional Optimal Order Detection (MOOD) method is an original Very High-Order Finite Volume (FV) method for conservation laws on unstructured meshes. The method is based on an a posteriori degree reduction of local polynomial reconstructions on cells where prescribed stability conditions are not fulfilled. Numerical experiments on advection and Euler equations problems are drawn to prove the efficiency and competitiveness of the MOOD method.

Mots clés: MOOD; high-order; finite volume; unstructured meshes; limitation; Euler equations; conservation laws

Domaines: Modélisation et simulation; Analyse numérique [math.NA]

Steven Diot, Stéphane Clain, Raphaël Loubère. Multi-dimensional Optimal Order Detection (MOOD) — A very high-order Finite Volume Scheme for conservation laws on unstructured meshes.. 2011. ⟨hal-00566023⟩