2000
DOI: 10.1016/s0376-0421(99)00013-5
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Parallel computing of overset grids for aerodynamic problems with moving objects

Abstract: Progress in Aerospace Sciences 36 (2000) 117-172. doi:10.1016/S0376-0421(99)00013-5Received by publisher: 0000-01-01Harvest Date: 2016-01-04 12:22:22DOI: 10.1016/S0376-0421(99)00013-5Page Range: 117-17

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Cited by 85 publications
(58 citation statements)
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“…The body-fitted and global grids were combined using a multi-blocked, overset-grid chimera scheme (Liu, 2009;Prewitt et al, 2000), which generated a virtual cubic water tank with a virtual swimming object submerged in the tank. Global grid cells whose centres fell within the body grid were emptied.…”
Section: Geometric Model and Grid Systemmentioning
confidence: 99%
“…The body-fitted and global grids were combined using a multi-blocked, overset-grid chimera scheme (Liu, 2009;Prewitt et al, 2000), which generated a virtual cubic water tank with a virtual swimming object submerged in the tank. Global grid cells whose centres fell within the body grid were emptied.…”
Section: Geometric Model and Grid Systemmentioning
confidence: 99%
“…Both solutions were interpolated at the boundary between both grids [30,[39][40][41]. We also interpolated areas of overlap within the bodyfitted grid that occurred when the fish's head and tail came close together.…”
Section: Hydrodynamic and Body Dynamic Solutionsmentioning
confidence: 99%
“…Many unsteady fluid flow simulations, such as fluid-structure interaction (FSI) [1][2][3] and wing-store separation [4], involve slight deformation of wall boundaries or relative motion between components in Computational Fluid Dynamics (CFD). This kind of problems is termed as dynamic mesh problems in unsteady calculations.…”
Section: Introductionmentioning
confidence: 99%
“…And the flow fluid simulations based on the traditional parallel techniques, such as MPI (message passing interface) [21] and OpenMP [22], have been studied in [3,4,6,9,11]. Since Nvidia's CUDA (Compute Unified Device Architecture) [23] was 2 Scientific Programming published in 2007, GPU computing has attracted more and more attention due to its high memory bandwidth and lightweighted threads of parallelism.…”
Section: Introductionmentioning
confidence: 99%