刘江凡,刘晓妹,李铮,等. 基于混合蒙特卡洛/多项式混沌展开方法的多参数随机等离子体不确定性分析[J]. 电波科学学报,2024,39(1):39-45. DOI: 10.12265/j.cjors.2023177
      引用本文: 刘江凡,刘晓妹,李铮,等. 基于混合蒙特卡洛/多项式混沌展开方法的多参数随机等离子体不确定性分析[J]. 电波科学学报,2024,39(1):39-45. DOI: 10.12265/j.cjors.2023177
      LIU J F, LIU X M, LI Z, et al. Multi-parametric stochastic plasma uncertainty quantification with a hybrid Monte-Carlo / polynomial chaos expansion method[J]. Chinese journal of radio science,2024,39(1):39-45. (in Chinese). DOI: 10.12265/j.cjors.2023177
      Citation: LIU J F, LIU X M, LI Z, et al. Multi-parametric stochastic plasma uncertainty quantification with a hybrid Monte-Carlo / polynomial chaos expansion method[J]. Chinese journal of radio science,2024,39(1):39-45. (in Chinese). DOI: 10.12265/j.cjors.2023177

      基于混合蒙特卡洛/多项式混沌展开方法的多参数随机等离子体不确定性分析

      Multi-parametric stochastic plasma uncertainty quantification with a hybrid Monte-Carlo / polynomial chaos expansion method

      • 摘要: 多项式混沌展开(polynomial chaos expansion, PCE)方法对于分析随机等离子体电磁传播不确定性已经展示出了相当大的潜力。然而,由于构建多项式混沌模型的计算量随着不确定性输入维数的增加呈指数增长,数值模拟耗时长,导致“维数灾难”问题。因此,本文基于非侵入式多项式混沌(non-intrusive polynomial chaos,NIPC)方法,采用混合蒙特卡洛(Monte Carlo, MC)/PCE方法研究了多层等离子体平板电子密度不确定性对透射系数的影响,并验证了所提出方法的实用性。与MC方法相比,本文方法可以大大加快仿真的速度,有效缓解了多项式展开项的数量随着随机变量维数的增加而快速增加的缺点,同时大大降低了MC方法的仿真次数,有利于电磁模型的多参数不确定性分析。

         

        Abstract: Polynomial chaotic expansion methods have shown considerable potential for analyzing the uncertainty of stochastic plasma electromagnetic propagation. However, because the amount of computation required to construct a polynomial chaotic model increases exponentially as the dimension of the uncertainty input variable increases, numerical simulations are time-consuming, resulting in the problem of "dimensional disaster". Thus, based on nonintrusive polynomial chaos(NIPC) method, the hybrid Monte Carlo/polynomial chaotic expansion(MC/PCE) method is used to study the effect of the multi-layer plasma flat-panel electron density uncertainty on transmission coefficient, which demonstrates the practicability of the proposed approach. By comparing it to the MC method, which can greatly accelerate the simulation speed, it is improved that the method effectively alleviates the rapid increase of the number of polynomial expansion terms with the increase of the dimension of random variables, and greatly reduces the number of simulations compared with Monte Carlo method, which is conducive to the multi-parameter uncertainty analysis of electromagnetic models.

         

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