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Massively Parallel GPU Implementation of the Lattice-Boltzmann Method for the Simulation of Coupled Aero-Thermodynamic Systems

机译:Lattice-Boltzmann方法的大规模并行GPU实现,用于仿真空气热力耦合系统

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The automotive industry is showing high demand for efficient design of cooling systems in electric vehicles. The development of complex aero-thermodynamic systems requires reliable, high-fidelity simulations of high Reynolds number flows. We implemented a numerical solver based on the double-distribution lattice-Boltzmann method (LBM). The main advantage of the LBM, compared to the Navier-Stokes-based solvers, is its computational efficiency and intrinsic parallelism, which allows for execution on massively parallel architectures (GPUs). We have validated our GPU implementation by simulating a natural convection flow and a heated cylinder in an enclosed cavity. Both cases show very good agreement with published literature. In the future, we aim to extend the usage of the LBM framework to industry-relevant cases like the simulation of various packaging concepts for electric vehicles.
机译:汽车行业对电动汽车冷却系统的高效设计显示出很高的需求。复杂的空气热力系统的发展需要高雷诺数流的可靠,高保真度模拟。我们基于双分布格子-玻尔兹曼方法(LBM)实现了数值求解器。与基于Navier-Stokes的求解器相比,LBM的主要优势在于其计算效率和固有的并行性,可在大规模并行体系结构(GPU)上执行。我们通过模拟自然对流和封闭腔体中的加热缸体来验证我们的GPU实现。两种情况都与已发表的文献非常吻合。未来,我们的目标是将LBM框架的使用范围扩展到与行业相关的案例,例如模拟电动汽车的各种包装概念。

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