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- W4317648955 abstract "Abstract We present an a posteriori shock-capturing finite volume method algorithm called GP-MOOD. The method solves a compressible hyperbolic conservative system at high-order solution accuracy in multiple spatial dimensions. The core design principle in GP-MOOD is to combine two recent numerical methods, the polynomial-free spatial reconstruction methods of GP (Gaussian Process) and the a posteriori detection algorithms of MOOD (Multidimensional Optimal Order Detection). We focus on extending GP’s flexible variability of spatial accuracy to an a posteriori detection formalism based on the MOOD approach. The resulting GP-MOOD method is a positivity-preserving method that delivers its solutions at high-order accuracy, selectable among three accuracy choices, including third-order, fifth-order, and seventh-order." @default.
- W4317648955 created "2023-01-21" @default.
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- W4317648955 date "2020-06-01" @default.
- W4317648955 modified "2023-09-29" @default.
- W4317648955 title "GP-MOOD: a positivity-preserving high-order finite volume method for hyperbolic conservation laws" @default.
- W4317648955 doi "https://doi.org/10.1017/s1743921322001363" @default.
- W4317648955 hasPublicationYear "2020" @default.
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