摘要
针对直接模拟蒙特卡洛(DSMC)方法统计耗散较大而传统的信息保存(DSMC-IP)方法难以有效模拟强激波的问题,采用对流迎风分裂(AUSM)通量计算格式对IP方法进行改造。以局部马赫数为标准重构控制方程中的关联项通量,使计算更加准确的符合激波两侧的流动特征,从而形成一种具有较高统计精度和高超声速流动模拟能力的新型DSMC-IP方法。采用该方法对超声速圆柱和带扩张角的喷管高超声速流动进行数值模拟,结果显示,该方法与DSMC方法的计算结果相比,其流场结构基本相符,而前者的统计耗散明显更低,且流动特征更清晰,表面特征系数与实验值或参考值相差在5.5%以内,证明了该方法在高超声速稀薄流场模拟中的准确性和有效性。
The Information Preservation(DSMC-IP)method is improved by using Advection Upstream Splitting Method(AUSM)splitting scheme,to solve the problems that the Direct Simulation of Monte Carlo(DSMC)method is effected by a large statistical dissipation,and that he traditional IP method cannot simulate the strong shock wave accurately.The fluxes of correlation terms in governing equations are reconstructed by local Mach numbers as the standard,so that the calculation is more accurate in accordance with the flow characteristics on both sides of the shock wave,thus forming a new DSMC-IP method with high statistical accuracy and hypersonic flow simulation ability.This method is utilized to simulate supersonic flow around the cylinder and hypersonic flow around the nozzle with divergent angle,the results of the AUSM splitting DSMC-IP method is basically consistent with the results of DSMC method,however the former has lower statistical scatter,and the flow characteristics are clearer.The surface characteristic coefficients differences between the results and the experiment or reference values are less than 5.5%.It is proved that the AUSM splitting DSMC-IP method is accurate and effective in the hypersonic flow simulation.
作者
许啸
马新建
张军
沈妍
XU Xiao;MA Xin-jian;ZHANG Jun;SHEN Yan(School of Mechatronics and Power Engineering,Jiangsu University of Science and Technology(Zhangjiagang),Zhenjiang 212003,China;Shanghai Academy of Spaceflight Technology,Academy of Aerospace Solid Propulsion Technology,Shanghai 201109,China;College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210001,China)
出处
《工程力学》
EI
CSCD
北大核心
2022年第1期228-242,共15页
Engineering Mechanics
基金
国家自然科学基金青年科学基金项目(11902125)
江苏省高等学校自然科学研究面上项目(18KJB130002)
国家重点研发计划项目(2018YFC0310400)。