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High-accurate SPH method with Multidimensional Optimal Order Detection limiting

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Detalhes bibliográficos
Resumo:We present a new high-accurate, stable and low-dissipative Smooth Particle Hydrodynamics (SPH) method based on Riemann solvers. The method derives from the SPH-ALE formulation first proposed by Vila and Ben Moussa. Moving Least Squares approximations are used for the reconstruction of the variables and the computation of Taylor expansions. The stability of the scheme is achieved by the a posteriori Multi-dimensional Optimal Order Detection (MOOD) paradigm. Such a procedure enables to provide genuine gains in accuracy both for one- and two-dimensional problems involving non-smooth flows when compared to classical SPH methods.
Autores principais:Nogueira, Xesús
Outros Autores:Ramı́rez, Luis; Clain, Stéphane; Loubère, Raphaël; Cueto-Felgueroso, Luis; Colominas, Ignasi
Assunto:High-order methods Smooth Particle Hydrodynamics Meshless methods Multi-dimensional Optimal Order Detection Moving Least Squares Ciências Naturais::Matemáticas
Ano:2016
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:We present a new high-accurate, stable and low-dissipative Smooth Particle Hydrodynamics (SPH) method based on Riemann solvers. The method derives from the SPH-ALE formulation first proposed by Vila and Ben Moussa. Moving Least Squares approximations are used for the reconstruction of the variables and the computation of Taylor expansions. The stability of the scheme is achieved by the a posteriori Multi-dimensional Optimal Order Detection (MOOD) paradigm. Such a procedure enables to provide genuine gains in accuracy both for one- and two-dimensional problems involving non-smooth flows when compared to classical SPH methods.