Three-dimensional conditional hyperbolic quadrature method of moments

Ravi G. Patel , Olivier Desjardins , Rodney O. Fox
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引用次数: 23

Abstract

The conditional hyperbolic quadrature method of moments (CHyQMOM) was introduced by Fox et al. [19] to reconstruct 1- and 2-D velocity distribution functions (VDF) from a finite set of integer moments. The reconstructed VDF takes the form of a sum of weighted Dirac delta functions in velocity phase space, and provides a hyperbolic closure for the spatial flux term in the corresponding moment equations derived from a kinetic equation for the 3-D VDF. Here, CHyQMOM is extended for 3-D velocity phase space using the modified conditional quadrature method of moments with 16 (or 23) trivariate velocity moments up to fourth order. In order to verify the numerical implementation, it is applied to simulate several canonical particle-laden flows including crossing jets, cluster-induced turbulence (CIT), and vertical channel flow. The numerical results are compared with those from Euler–Lagrange simulations and two other quadrature-based moment methods, namely, anisotropic Gaussian (AG) and 8-node tensor-product (TP) quadrature. The relative advantages and disadvantages of each method are discussed. The crossing-jet problem highlights that CHyQMOM handles particle crossing more accurately than AG. For CIT, the results from all methods are similar, but the computational cost of TP is significantly larger than AG and CHyQMOM, both of which have nearly the same cost.

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三维条件双曲矩求积法
Fox等人[19]引入了矩的条件双曲求积法(CHyQMOM),用于从有限的整数矩集重建一维和二维速度分布函数(VDF)。重建的VDF采用速度相空间中的加权Dirac delta函数之和的形式,并为从3-D VDF的动力学方程导出的相应力矩方程中的空间通量项提供双曲闭包。这里,使用具有16(或23)个高达四阶的三元速度矩的矩的修正条件求积方法,将CHyQMOM扩展到三维速度相空间。为了验证数值实现,将其应用于模拟几种典型的含颗粒流,包括交叉射流、团簇诱导湍流(CIT)和垂直通道流。将数值结果与欧拉-拉格朗日模拟和其他两种基于正交的矩方法,即各向异性高斯(AG)和8节点张量积(TP)正交的结果进行了比较。讨论了每种方法的相对优缺点。交叉射流问题突出表明,CHyQMOM比AG更准确地处理粒子交叉。对于CIT,所有方法的结果都相似,但TP的计算成本明显大于AG和CHyQMOM,两者的成本几乎相同。
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来源期刊
Journal of Computational Physics: X
Journal of Computational Physics: X Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
6.10
自引率
0.00%
发文量
7
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