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首页> 外文期刊>Journal of Computational Physics >Searching for a near neighbor particle in DSMC cells using pseudo-subcells
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Searching for a near neighbor particle in DSMC cells using pseudo-subcells

机译：使用伪子单元在DSMC单元中搜索近邻粒子

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LeBeau et al. (2003) [4] introduced the 'virtual-subcell' (VSC) method of finding a collision partner for a given DSMC particle in a cell; all potential collision partners in the cell are examined to find the nearest neighbor, which becomes the collision partner. Here I propose a modification of the VSC method, the 'pseudo-subcell' (PSC) method, whereby the search for a collision partner stops whenever a 'near-enough' particle is found, i.e. whenever another particle is found within the 'pseudo-subcell' of radius δ centered on the first particle. The radius of the pseudo-subcell is given by δ=Fd_n, where d_n is the expected distance to the nearest neighbor and F is a constant which can be adjusted to give a desired trade-off between CPU time and accuracy as measured by a small mean collision separation (MCS). For 3D orthogonal cells, of various aspect ratios, d_n/L≈0.746/N~(0.383) where N is the number of particles in the cell and L is the cube root of the cell volume. There is a good chance that a particle will be found in the pseudo-subcell and there is a good chance that such a particle is in fact the nearest neighbor. If no particle is found within the pseudo-subcell the closest particle becomes the collision partner.To limit the CPU time required for large . N the search is restricted to a subset of all particles in the cell; the nearest particle from that subset becomes the collision partner. Here the VSC search is restricted to 29 of the remaining particles and the CPU time never increases beyond what is required for . N=. 30. For . N>. 30 the restricted search is as accurate as a standard subcell method using 34 subcells in a 3D cell. The PSC search surveys up to 33 possible collision partners, to yield the same limiting value of MCS, and still save some CPU time. For . F=. 1.1, PSC uses between 12% and 20% less CPU than VSC while the accuracy is within 4% of that for VSC.
机译：LeBeau等。 （2003）[4]引入了“虚拟子细胞”（VSC）方法，该方法为细胞中给定的DSMC粒子寻找碰撞伴侣。检查单元中所有潜在的碰撞伙伴，以找到最近的邻居，该邻居成为碰撞伙伴。在这里，我提议对VSC方法的一种改进，即“伪子电池”（PSC）方法，通过这种方法，只要找到“近乎足够”的粒子，即每当在“伪”中找到另一个粒子，搜索伙伴就停止搜索。半径δ的'subcell'以第一个粒子为中心。伪子单元的半径由δ= Fd_n给出，其中d_n是到最近邻居的预期距离，F是可以调整的常数，可以在CPU时间和精度之间进行所需的权衡，以较小的方式衡量平均碰撞分离（MCS）。对于各种纵横比的3D正交像元，d_n /L≈0.746/ N〜（0.383），其中N是像元在细胞中的数量，L是像元体积的立方根。很可能在伪子单元中找到一个粒子，并且很可能这样的粒子实际上是最近的邻居。如果在伪子单元格中未找到任何粒子，则最接近的粒子将成为碰撞伙伴。要限制large所需的CPU时间。 N搜索仅限于单元中所有粒子的子集;该子集中最接近的粒子成为碰撞伙伴。在这里，VSC搜索仅限于剩余粒子中的29个，并且CPU时间永远不会超过所需的时间。 N =。 30.对于。 N>。 30受限搜索与在3D单元中使用34个子单元的标准子单元方法一样准确。 PSC搜索最多可调查33个可能的碰撞伙伴，以产生相同的MCS极限值，并且仍节省一些CPU时间。对于。 F =。如图1.1所示，PSC使用的CPU比VSC少12％到20％，而准确度仅为VSC的4％之内。

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