The unified stochastic particle method based on the Bhatnagar-Gross-Krook model (USP-BGK) has been proposed recently to overcome the low accuracy and efficiency of the traditional stochastic particle methods, such as the direct simulation Monte Carlo (DSMC) method, for the simulation of multi-scale gas flows. However, running with extra virtual particles and space interpolation, the previous USP-BGK method cannot be directly transplanted into the existing DSMC codes. In this work, the implementation of USP-BGK is simplified using new temporal evolution and spatial reconstruction schemes. As a result, the present algorithm of the USP-BGK method is similar to the DSMC method and can be implemented efficiently based on any existing DSMC codes just by modifying the collision module.

中文翻译：

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一种高效的统一随机粒子Bhatnagar-Gross-Krook方法模拟多尺度气流的算法

最近提出了基于 Bhatnagar-Gross-Krook 模型 (USP-BGK) 的统一随机粒子方法，以克服直接模拟蒙特卡罗 (DSMC) 方法等传统随机粒子方法的精度和效率低下的问题。多尺度气体流动的模拟。但是，运行额外的虚拟粒子和空间插值，之前的USP-BGK方法不能直接移植到现有的DSMC代码中。在这项工作中，使用新的时间演化和空间重建方案简化了 USP-BGK 的实施。因此，USP-BGK 方法的本算法类似于 DSMC 方法，只需修改碰撞模块即可基于任何现有的 DSMC 代码高效实现。