The Test Particle Monte Carlo is a known method to solve the steady state Boltzmann particle transport equation in rarefied gas systems. A description of the Test Particle Monte-Carlo procedure is outlined and the accuracy of this method is investigated by analyzing its consistency to experimental data of steady state effusions in isothermal systems. Computational results present deviations from the experiments that are at most 6.7%. After which, this paper investigates the potential of this method when it is parallelized using multi-core CPUs with shared memory for large Knudsen numbers. Scalability is expected since the method relies on a mean particle field that renders particle trajectories nearly independent from one another, therefore reducing data communication between processing cores. The mean particle distribution field helps linearize the collision term of the Boltzmann equation. Shared Memory Parallelism is an interesting feature when combined with distributed memory parallelism for design optimization of vacuum systems.

测试粒子蒙特卡罗是求解稀薄气体系统中稳态玻尔兹曼粒子传输方程的已知方法。概述了测试粒子蒙特卡罗程序的描述，并通过分析其与等温系统中稳态流出实验数据的一致性来研究该方法的准确性。计算结果与实验的偏差最多为 6.7%。之后，本文研究了该方法在使用具有共享内存的多核 CPU 并行化处理大型 Knudsen 数时的潜力。由于该方法依赖于使粒子轨迹几乎彼此独立的平均粒子场，因此可预期可扩展性，因此减少了处理核心之间的数据通信。平均粒子分布场有助于线性化 Boltzmann 方程的碰撞项。当与分布式内存并行性相结合以优化真空系统的设计时，共享内存并行性是一个有趣的功能。