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A GPU-accelerated solver for turbulent flow and scalar transport based on the Lattice Boltzmann method

机译:基于晶格Boltzmann方法的湍流和标量传输的GPU加速求解器

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摘要

In this article, we apply the Vreman model with a dynamic procedure for subgrid scale modeling of turbulent flow and scalar transport under the Lattice Boltzmann framework. Numerical results of two types of typical turbulent flow systems are presented and discussed, i.e., the channel Poiseuille flow with heat transfer, and the Rayleigh-Taylor convection. Due to their intrinsic differences, analyses of the two turbulent phenomena are carried out mainly according to the statistical averaging property and the temporal evolution process, respectively. The feasibility and accuracy of the present turbulent solver is validated via comparisons with direct numerical simulation results and theoretical predictions. In addition, the GPU parallel technique is applied and yields a very efficient solver for turbulent flow and scalar transport, and the algorithm is introduced in detail. Overall, our work offers a useful extension of the current Lattice Boltzmann method and a powerful tool for turbulent modeling.
机译:在本文中,我们将VREMAMED模型应用于在格子Boltzmann框架下的湍流流量和标量传输的细分规模建模的动态程序。提出和讨论了两种类型的典型湍流流量系统的数值结果,即,具有传热的通道Poiseuille流,以及瑞利泰勒对流。由于它们的内在差异,分析了两种湍流现象的分析分别根据统计平均值和时间进化过程进行。目前湍流求解器的可行性和准确性通过与直接数值模拟结果和理论预测的比较验证。另外,施加GPU并行技术,并产生一个非常有效的求解器,用于湍流和标量传输,并详细介绍该算法。总体而言,我们的作品提供了当前格子Boltzmann方法的有用扩展,以及湍流建模的强大工具。

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