论文标题

用于预测稀有和多尺度流的一般离散速度框架的全球自适应速度空间

A global adaptive velocity space for general discrete velocity framework in predictions of rarefied and multi-scale flows

论文作者

Chen, Jianfeng, Liu, Sha, Zhang, Rui, Zhong, Chengwen, Yang, Yanguang, Zhuo, Congshan

论文摘要

稀有流量和多尺度流对于航天器,超低轨道车辆和羽流的空气动力学设计至关重要。通过引入离散速度空间,诸如离散速度方法和统一方法之类的玻尔兹曼方法可以捕获复杂和非平衡速度分布函数(VDFS),并准确地描述流动行为。但是,在局部粒子速度空间中,极度陡峭的斜率和高浓度的气体VDF使得具有结构化速度空间的玻尔兹曼方法很难描述高速流​​量。因此,需要自适应速度空间(AV)才能使玻尔兹曼求解器在复杂的稀疏流和多尺度流动中实用。本文对AVS方法进行了两个改进,然后将其纳入一般离散速度框架中,例如统一的气体运动方案。首先,使用一个全局速度网格来防止在微观通量计算过程中VDF在物理界面处的插值,从而保持程序的高水平并行性。其次,新速度空间上的VDF不是使用``血管性''关系重建。换句话说,分裂的子节点的VDF与父母的VDF相同,并且是其合并的父母的VDF的平均差异,而eDection distection的平均差异是iSSIDERIPATION的平均差异。此外,还建立了一组适当的自适应参数,以增强所提出的方法的自动化。

The rarefied flow and multi-scale flow are crucial for the aerodynamic design of spacecraft, ultra-low orbital vehicles and plumes. By introducing a discrete velocity space, the Boltzmann method, such as the discrete velocity method and unified methods, can capture complex and non-equilibrium velocity distribution functions (VDFs) and describe flow behaviors exactly. However, the extremely steep slope and high concentration of the gas VDFs in a local particle velocity space make it very difficult for the Boltzmann method with structured velocity space to describe high speed flow. Therefore, the adaptive velocity space (AVS) is required for the Boltzmann solvers to be practical in complex rarefied flow and multi-scale flow. This paper makes two improvements to the AVS approach, which is then incorporated into a general discrete velocity framework, such as the unified gas-kinetic scheme. Firstly, a global velocity mesh is used to prevent the interpolation of the VDFs at the physical interface during the calculation of the microscopic fluxes, maintaining the program's high level of parallelism. Secondly, rather than utilizing costly interpolation, the VDFs on a new velocity space were reconstruction using the ``consanguinity" relationship. In other words, a split child node's VDF is the same as its parent's VDF, and a merged parent's VDF is the average of its children's VDFs. Additionally, the discrete deviation of the equilibrium distribution functions is employed to maintain the proposed method's conservation. Moreover, an appropriate set of adaptive parameters is established to enhance the automation of the proposed method. Finally, a number of numerical tests are carried out to validate the proposed method.

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