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A solution algorithm for the fluid dynamic equations based on a stochastic model for molecular motion

机译:基于分子运动随机模型的流体动力学方程组求解算法

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In this paper, a stochastic model is presented to simulate the flow of gases, which are not in thermodynamic equilibrium, like in rarefied or micro situations. For the interaction of a particle with others, statistical moments of the local ensemble have to be evaluated, but unlike in molecular dynamics simulations or DSMC, no collisions between computational particles are considered. In addition, a novel integration technique allows for time steps independent of the stochastic time scale. The stochastic model represents a Fokker-Planck equation in the kinetic description, which can be viewed as an approximation to the Boltzmann equation. This allows for a rigorous investigation of the relation between the new model and classical fluid and kinetic equations. The fluid dynamic equations of Navier-Stokes and Fourier are fully recovered for small relaxation times, while for larger values the new model extents into the kinetic regime. Numerical studies demonstrate that the stochastic model is consistent with Navier-Stokes in that limit, but also that the results become significantly different, if the conditions for equilibrium are invalid. The application to the Knudsen paradox demonstrates the correctness and relevance of this development, and comparisons with existing kinetic equations and standard solution algorithms reveal its advantages. Moreover, results of a test case with geometrically complex boundaries are presented.
机译:在本文中,提出了一种随机模型来模拟气体流动,这些气体不处于热力学平衡状态,例如在稀疏或微观情况下。对于粒子与其他粒子的相互作用,必须评估局部集合的统计矩,但是与分子动力学模拟或DSMC不同,计算粒子之间不存在碰撞。另外,一种新颖的积分技术允许独立于随机时间标度的时间步长。随机模型表示动力学描述中的Fokker-Planck方程,可以将其视为对Boltzmann方程的近似。这允许对新模型与经典流体和动力学方程之间的关系进行严格研究。 Navier-Stokes和Fourier的流体动力学方程在较小的弛豫时间就可以完全恢复,而对于较大的值,新模型可以进入动力学范围。数值研究表明,在该极限下,随机模型与Navier-Stokes一致,而且,如果平衡条件无效,则结果也将显着不同。在Knudsen悖论上的应用证明了这一发展的正确性和相关性,并且与现有的动力学方程式和标准解算法进行比较表明了其优势。此外,还介绍了具有几何复杂边界的测试案​​例的结果。

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