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- W2112778387 abstract "Particle tracking methods are a versatile computational technique central to the simulation of a wide range of scientific applications. In this paper we present an a posteriori error estimator for adaptive mesh refinement (AMR) using particle tracking methods. The approach uses a parallel computing framework, the in-element particle tracking method, based on the assumption that particle trajectories are computed by problem data localized to individual elements. Adaptive mesh refinement is used to control the mesh discretization errors along computed characteristics of the particle trajectories. Traditional a posteriori error estimators for AMR methods inherit flaws from the discrete solution of time-marching partial differential equations (PDEs)--particularly for advection/convection-dominated transport applications. To address this problem we introduce a new a posteriori error estimator based on particle tracking methods. We present experimental results that detail the performance of a parallel implementation of this particle method approach for a two-dimensional, time-marching convection-diffusion benchmark problem on an unstructured, adaptive mesh." @default.
- W2112778387 created "2016-06-24" @default.
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- W2112778387 date "2003-01-01" @default.
- W2112778387 modified "2023-09-23" @default.
- W2112778387 title "An A Posteriori Error Estimator for Adaptive Mesh Refinement Using Parallel In-Element Particle Tracking Methods" @default.
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- W2112778387 doi "https://doi.org/10.1007/3-540-36569-9_7" @default.
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