期刊文献+

直接模拟蒙特卡罗方法下的逆温度抽样算法 被引量:3

Inverse Temperature Sampling under Direct Simulation Monte Carlo Method
下载PDF
导出
摘要 从分子动力学出发,讨论了直接模拟蒙特卡罗方法中分子平均总能量、平均平动能以及边界热流密度的抽样方法.通过对与边界发生碰撞的分子进行统计平均,得到了分子反射能量与入射能量以及边界热流密度的关系式.在此基础上,通过结合壁面漫反射模型下分子反射速度的抽样方法,发展了一种从边界热流求得与壁面碰撞分子的平均反射特征温度的逆温度抽样算法.数值结果表明:该算法能够由分子反射能量准确求得分子反射特征温度,进而求得分子反射速度,从而将边界热流信息带入流场.该方法为实现壁面处给定热流边界条件下的直接模拟蒙特卡罗方法提供了途径. Based on the principle of molecular dynamics, a sampling method in Direct Simulation Monte Carlo (DSMC) method for molecular total and translational energy, and the heat flux vector nearby the wall boundary is proposed. An important relationship among the mean incident energy, reflective energy and the wall boundary heat flux is obtained by statistically averaging the energy values of those molecules colliding with wall. Combining the generating method of molecular reflective thermal velocities according to diffuse reflection model, an algorithm named as Inverse Temperature Sampling (ITS) is developed, which enables to evaluate the molecular reflective characteristic temperature from the molecular incident energy and the boundary heat flux. The numerical results show that the molecular reflective temperature is accurately sampled with this algorithm, thus the information of heat flux at wall boundary is imposed to the flow field. In this way, the constant heat flux boundary condition in DSMC method can be implemented.
出处 《西安交通大学学报》 EI CAS CSCD 北大核心 2006年第1期22-25,共4页 Journal of Xi'an Jiaotong University
基金 国家自然科学基金资助项目(50376050 50476088)
关键词 逆温度抽样算法 给定热流边界 直接模拟蒙特卡罗 inverse temperature sampling constant heat flux boundary direct simulation MonteCarlo
  • 相关文献

参考文献9

  • 1Bird G A. Molecular gas dynamics and the direct simulation of gas flows [M]. Oxford: Clarendon Press,1994.
  • 2Nance R P, Hash D B, Hassan H A. Role of boundary conditions in Monte Carlo simulation of microelectromechanical systemes [J]. Journal of Thermophysics and Heat Transfer, 1998, 12(3): 447-449.
  • 3Oran E S, Oh C K, Cybyk B Z. Direct simulation Monte Carlo: recent advances and applications [J].Annul Review of Fluid Mechanics, 1998, 30 (1) :403-441.
  • 4Bird G A. Recent advances and current challenges for DSMC [J]. Computers & Mathematics with Applications, 1998, 35(1):1-14.
  • 5Fan J, Shen C. Statistical simulation of low-speed rarefied gas flows [J]. Journal of Computational Physics,2001, 167(1): 393-412.
  • 6Cai C P, Boyd I D, Fan J, et al. Direct simulation methods for low-speed mieroehannel flows [J]. Journal of Thermophysics and Heat Transfer, 2000, 14(3) : 368-378.
  • 7Pan L S, Liu G R, Khoo B C, et al. A modified direct simulation Monte Carlo method for low-speed micro flows [J]. Journal of Micromechanics and Microengineering, 2000, 10(1) : 21-27.
  • 8Fang Y, Liou W W. Computations of the flow and heat transfer in microdevices using DSMC with implicit boundary conditions [J]. Journal of Heat Transfer,2002, 24(2):338-345.
  • 9He Q W, Wang Q W, Wang X, et al. Computational investigation of low-speed gas flow and heat transfer in micro-channel using DSMC with pressure boundary condition [A]. Advanced Computational Method in Heat Transfer:Ⅷ [C]. Southampton: WIT Press,2004。463-469.

同被引文献25

引证文献3

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部