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如何更高效发挥减方差的作用是蒙特卡罗方法在先进核能系统屏蔽分析应用中的研究热点之一。本文发展了一种基于自动网格划分与权窗平滑的自适应减方差方法,在蒙特卡罗和确定论耦合的一致性伴随驱动的重要性抽样方法(Consistent Adjoint Driven Importance Sampling,CADIS)基础上,利用计算机辅助设计(Computer Aided Design,CAD)自动转换和自由程自动划分SN网格,通过确定论方法伴随预计算,实现基于伴随通量的区域权窗参数自动配置,并对伴随通量变化剧烈区域进行权窗平滑处理,保证了粒子在不同区域的有效偏倚,进一步提高计算的效率,从而解决大空间蒙特卡罗计算难以收敛的问题。该方法已初步应用于中国铅基反应堆(China Lead-based Reactor,CLEAR)堆顶盖的屏蔽计算分析,该案例具有结构复杂、屏蔽材料厚重的特点,测试结果表明本方法将计算效率提高近10倍。
How to exert the effect of reducing the variance more efficiently is one of the hot topics in the application of shielding analysis of advanced nuclear energy system by Monte Carlo method. Based on the Consistent Adjoint Driven Importance Sampling (CADIS) method for the Monte Carlo-deterministic coupling-driven coincidence driven driving, this paper develops a method of adaptive minus variance based on auto- , Automatic partitioning of SN grids by computer aided design (CAD) auto-transition and free-range is performed. Autoconfiguration of region-based rights window parameters based on the companion flux is realized by deterministic method with precompute. Violent window smoothing is carried out in violent areas to ensure the effective biases of particles in different areas and to further improve the computational efficiency so as to solve the problem of difficult convergence in large space Monte Carlo calculations. This method has been initially applied to the shield calculation of China Lead-based Reactor (CLEAR) heap. The case has the characteristics of complex structure and thick shielding materials. The test results show that this method can improve the computational efficiency by nearly 10 Times