Large eddy simulation of turbulent flow using the parallel computational fluid dynamics code GASFLOW-MPI

GASFLOW-MPI is a widely used scalable computational fluid dynamics numerical tool to simulate the fluid turbulence behavior, combustion dynamics, and other related thermal–hydraulic phenomena in nuclear power plant containment. An efficient scalable linear solver for the large-scale pressure equatio...

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Veröffentlicht in:Nuclear engineering and technology 2017-09, Vol.49 (6), p.1310-1317
Hauptverfasser: Zhang, Han, Li, Yabing, Xiao, Jianjun, Jordan, Thomas
Format: Artikel
Sprache:eng
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Zusammenfassung:GASFLOW-MPI is a widely used scalable computational fluid dynamics numerical tool to simulate the fluid turbulence behavior, combustion dynamics, and other related thermal–hydraulic phenomena in nuclear power plant containment. An efficient scalable linear solver for the large-scale pressure equation is one of the key issues to ensure the computational efficiency of GASFLOW-MPI. Several advanced Krylov subspace methods and scalable preconditioning methods are compared and analyzed to improve the computational performance. With the help of the powerful computational capability, the large eddy simulation turbulent model is used to resolve more detailed turbulent behaviors. A backward-facing step flow is performed to study the free shear layer, the recirculation region, and the boundary layer, which is widespread in many scientific and engineering applications. Numerical results are compared with the experimental data in the literature and the direct numerical simulation results by GASFLOW-MPI. Both time-averaged velocity profile and turbulent intensity are well consistent with the experimental data and direct numerical simulation result. Furthermore, the frequency spectrum is presented and a –5/3 energy decay is observed for a wide range of frequencies, satisfying the turbulent energy spectrum theory. Parallel scaling tests are also implemented on the KIT/IKET cluster and a linear scaling is realized for GASFLOW-MPI.
ISSN:1738-5733
DOI:10.1016/j.net.2017.08.003