کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7156022 1462641 2018 59 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of adaptively refined unstructured grids in DSMC to shock wave simulations
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Application of adaptively refined unstructured grids in DSMC to shock wave simulations
چکیده انگلیسی
An efficient, new DSMC framework based on AMR/octree unstructured grids is demonstrated for the modeling of near-continuum, strong shocks in hypersonic flows. The code is able to capture the different length scales in such flows through the use of a linearized representation of the unstructured grid using Morton-Z space filling curve for efficient access of collision cells. Strategies were developed to achieve a strong scaling of nearly ideal speed up to 4096 processors and 87% efficiency (weak scaling) for 8192 processors for a strong shock created by flow over a hemisphere. To achieve these very good scalings, algorithms were developed to weight the computational work of a processor by the use of profiled run time data, create maps to optimize processor point-to-point communications, and efficiently generate new DSMC particles every time step. Rigorous thermal non-equilibrium required for modeling high Mach number shocks was achieved through the accurate modeling of collision temperatures on a sampling grid designed to be compatible with the above approaches. The simulation of a nitrogen flow over a double wedge configuration for near-continuum conditions revealed complex hypersonic SWBLIs as well as three-dimensional gas-surface kinetic effects such as velocity and temperature slip. The simulations showed that three-dimensional effects are important in predicting the size of the separation bubble, which in turn, influences gas-surface measurements such as pressure and heat flux.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Fluids - Volume 170, 15 July 2018, Pages 197-212
نویسندگان
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