论文标题
降低和噪声源采样技术，用于由机械振动引起的中子噪声的蒙特卡洛模拟
Variance Reduction and Noise Source Sampling Techniques for Monte Carlo Simulations of Neutron Noise Induced by Mechanical Vibrations
论文作者
论文摘要
核功率反应堆中的中子噪声是指由于核心内部的时间依赖性扰动而导致的稳态中的平均中子通量周围的小波动。频域中的中子噪声方程可以使用蒙特卡洛模拟代码来解决，这些代码能够获得涉及几乎没有近似值的参考解决方案，但受到影响统计收敛的严重问题的阻碍：同时存在正面和负面粒子，这是由于复杂噪声方程的性质所需要的，从而导致较大的较大的差异，从而导致较大的差异。在这项工作中，我们考虑了机械振动引起的中子噪声问题的重要情况。首先，我们为噪声源得出了一种新的精确采样策略。然后，基于我们以前在其他情况下的发现，我们表明，取消体重的方法可能对处理负重的存在非常有益，从而在功绩中实现了极大的收益。我们在由带有振动引脚的燃料组件组成的基准配置上成功证明了我们的结果，我们讨论了可能进一步改进的途径。
Neutron noise in nuclear power reactors refers to the small fluctuations around the average neutron flux at steady state resulting from time-dependent perturbations inside the core. The neutron noise equations in the frequency domain can be solved using Monte Carlo simulation codes, which are capable of obtaining reference solutions involving almost no approximations, but are hindered by severe issues affecting the statistical convergence: the simultaneous presence of positive and negative particles, which is required by the nature of the complex noise equations, leads to catastrophically large variance in the tallies. In this work, we consider the important case of neutron noise problems induced by mechanical vibrations. First, we derive a new exact sampling strategy for the noise source. Then, building upon our previous findings in other contexts, we show that weight cancellation methods can be highly beneficial in dealing with the presence of negative weights, enabling extremely large gains in the figure of merit. We successfully demonstrate our results on a benchmark configuration consisting of a fuel assembly with a vibrating pin and we discuss possible pathways for further improvements.
