Abstract
Computational fluid dynamic (CFD) computations are memory and time intensive and need to be executed in parallel for larger computational domains. In order to produce physical accurate solutions, adaptive grid setups have to be chosen as the memory and computing time would otherwise be too high, and results would not be obtained in a reasonable amount of time. This paper describes the usage of a multi-grid based approach for solving the pressure Poisson equation, arising during every time step of the Navier-Stokes equations. It will then highlight an analysis of errors introduced due to an adaptive setup of the domain, and show performance measurements for uniform and adaptive grid setups. Last but not least, a CFD benchmark example based on the von K\'{a}rm\'{a}n vortex street will be presented, and the results will be discussed.
Highlights
Computational fluid dynamics (CDF) simulations are time intensive and require a lot of computational resources
In order to evaluate the performance as well as the accuracy of the used data structures and its solvers, a Poisson equation will be solved for a simple test geometry
The authors presented a detailed study about an adaptive layout for a parallel distributed data structure capable of computing fluid flow simulations, as well as the main idea of a multi-grid based solver approach
Summary
Computational fluid dynamics (CDF) simulations are time intensive and require a lot of computational resources. The neighbourhood server contains all management grids and can compute the best possible data distribution according to a certain given strategy. The multi-grid like concept needs more smoothing steps in order to converge to the correct solution, especially when obstacles are present in the domain.
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