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中文摘要：
用蒙特卡罗（MC）方法模拟高温、高压、多介质、大变形辐射输运问题时,由于网格体积悬殊,导致各网格通量的统计误差涨落很大,随着时间步的增加,误差积累甚至会导致计算结果失真.为此,发展了针对全局网格计算的源偏倚抽样技巧.用于源偏倚抽样的价值函数基于上个时间步各网格通量及误差,通过加权构造产生,它比传统MC通过解伴随方程获取价值的性价比要高得多.数值试验表明,全局源偏倚抽样通过自适应分配当前时间步各网格的粒子数,有效地降低了当前步重要网格通量误差.
英文摘要：
Monte Carlo method is used to simulate the radiation transport problems which have characteristics of high temperature,high pressure,multi-media and large deformation of the grid. Due to the nonuniform particle distribution and great difference in the sizes of the grid,it makes the statistical errors of the grid fluxes fluctuate wildly. The error accumulation after many time steps may even influence the truth of the calculated results. So the global source biasing technique is developed. The importance function used here for source biasing sampling is based on the grid fluxes and errors of the previous time step. This is much faster than the traditional methods for solving the adjoint equation. The numerical tests showed that the neutron flux errors in the important grids are obviously reduced by using global source biasing which adaptively assigns the number of particles in each grid.
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