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Numerical Solution of the Taylor-Quette Flow Problem: A Commodious Statistical Approach | Science Publications

机译：泰勒-奎特流问题的数值解：一种统计方法科学出版物

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> Problem statement: The main problem in solving of the Boltzmann equation by statistical methods is its long computational time (CPU time). The problem of decreasing of CPU time usage in statistical solution methods of Boltzmann equation for rarefied vortex flows was studied. Approach: In this study the Boltzmann equation in a rarefied Taylor-Quette flow regime was solved using the new Monte Carlo method which is officially named time Relaxated Mont Carlo method that applied the equilibrium conditions in each time step. Results: The results obtained from time Relaxated Mont Carlo method for the problem at hand were compared with those from the usual Direct Simulation Monte Carlo method. This comparison showed good agreement between the two sets of results. Conclusion: Whereas, the number of collisions and CPU usage time in the suggested method, as compared to the direct simulation Monte Carlo method, showed a significant decrease.
机译： > 问题陈述：用统计方法求解玻尔兹曼方程的主要问题是计算时间长（CPU时间）。研究了稀疏涡流的玻尔兹曼方程统计解法中减少CPU使用时间的问题。 方法：在这项研究中，使用新的蒙特卡洛方法（正式命名为时间松弛蒙特卡洛方法）求解稀疏泰勒-奎特流态中的玻尔兹曼方程，该方法在每个时间步均应用了平衡条件。 结果：将通过时间松弛Mont Carlo方法获得的有关当前问题的结果与通常的直接模拟Monte Carlo方法获得的结果进行了比较。该比较表明两组结果之间有很好的一致性。 结论：与直接模拟蒙特卡洛方法相比，建议方法中的冲突次数和CPU使用时间显着减少。

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