Add to ORKGThe Multi-dimensional Optimal Order Detection (MOOD) method has been designed by authors in [5] and extended in [7] to reach Very-High-Order of accuracy for systems of Conservation Laws in a Finite Volume (FV) framework on 2D unstructured meshes. In this paper we focus on the extension of this method to 3D unstructured meshes. We present preliminary results for the three-dimensional advection equation which confirm the good behaviour of the MOOD method. More precisely, we show that the scheme yields up to sixth-order accuracy on smooth solutions while preventing oscillations from appearing on discontinuous profiles
In this paper a relaxed formulation of the a posteriori Multi-dimensional Optimal Order Detection (M...
Os datos relativos aos resultados deste artigo poden descargarse desde https://doi.org/10.17862/cran...
In this paper the relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is ...
The Multi-dimensional Optimal Order Detection (MOOD) method has been designed by authors in [5] and ...
The Multi-dimensional Optimal Order Detection (MOOD) method has been designed by authors in [5] and ...
Preprint for Finite Volume for Complex Applications 6 (FVCA6)The Multi-dimensional Optimal Order Det...
The Multi-dimensional Optimal Order Detection (MOOD) method for two-dimensional geometries has been ...
International audienceIn this paper, we investigate an original way to deal with the problems genera...
The Multi-dimensional Optimal Order Detection (MOOD) method is an original Very High-Order Finite ...
International audienceIn this paper, we investigate the coupling of the Multi-dimensional Optimal Or...
In this paper, we investigate an original way to deal with the problems generated by the limitation...
The Multidimensional Optimal Order Detection (MOOD) method for two-dimensional geometries has been i...
This paper extends the MOOD method proposed by the authors in ["A high-order finite volume method fo...
This paper extends the MOOD method proposed by the authors in [A high-order finite volume method f...
We present an a posteriori shock-capturing finite volume method algorithm called GP-MOOD that solves...
In this paper a relaxed formulation of the a posteriori Multi-dimensional Optimal Order Detection (M...
Os datos relativos aos resultados deste artigo poden descargarse desde https://doi.org/10.17862/cran...
In this paper the relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is ...
The Multi-dimensional Optimal Order Detection (MOOD) method has been designed by authors in [5] and ...
The Multi-dimensional Optimal Order Detection (MOOD) method has been designed by authors in [5] and ...
Preprint for Finite Volume for Complex Applications 6 (FVCA6)The Multi-dimensional Optimal Order Det...
The Multi-dimensional Optimal Order Detection (MOOD) method for two-dimensional geometries has been ...
International audienceIn this paper, we investigate an original way to deal with the problems genera...
The Multi-dimensional Optimal Order Detection (MOOD) method is an original Very High-Order Finite ...
International audienceIn this paper, we investigate the coupling of the Multi-dimensional Optimal Or...
In this paper, we investigate an original way to deal with the problems generated by the limitation...
The Multidimensional Optimal Order Detection (MOOD) method for two-dimensional geometries has been i...
This paper extends the MOOD method proposed by the authors in ["A high-order finite volume method fo...
This paper extends the MOOD method proposed by the authors in [A high-order finite volume method f...
We present an a posteriori shock-capturing finite volume method algorithm called GP-MOOD that solves...
In this paper a relaxed formulation of the a posteriori Multi-dimensional Optimal Order Detection (M...
Os datos relativos aos resultados deste artigo poden descargarse desde https://doi.org/10.17862/cran...
In this paper the relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is ...