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Spectrum Adjustment Results for Three Environments in the ACRR Central Cavity Using a Genetic Algorithm

机译:使用遗传算法,频谱调整为ACRR中央腔中的三种环境

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Presented in this report is the description of a new method for neutron energy spectrum adjustment that uses a genetic algorithm to minimize the difference between calculated and measured reaction probabilities. The reaction probability is the integral over all energies of the product of the microscopic reaction cross section with the neutron fluence. The measured reaction probabilities are found using neutron activation analysis. The method adjusts a trial spectrum provided by the user that typically is calculated using a neutron transport code such as Monte Carlo N-Particle. Observed benefits of this method over currently existing methods include: (a) the reduction in unrealistic artifacts in the spectral shape when compared to iterative unfold approaches such as are used in the SAND-II code or to least squares approaches when an accurate prior spectrum covariance is not available; and (b) a reduced sensitivity to increases in the energy resolution of the derived spectrum. This report presents the adjustment results for various spectrum-altering bucket environments in the central cavity of the Annular Core Research Reactor. In each case, the results are compared to those generated using LSL-M2, which is a code commonly used for spectrum adjustment. The genetic algorithm produces spectrum-averaged reaction probabilities comparable to those resulting from LSL-M2. The splicing of local segments of the a priori spectrum, which is part of the genetic algorithm, permits the resulting spectrum adjustment to avoid introducing severe narrow energy-width shape artifacts without the requirement of a covariance matrix for the prior spectrum.
机译:在本报告中呈现的是使用遗传算法来描述使用遗传算法来最小化计算和测量的反应概率之间的差异的新方法。反应概率是微观反应横截面的所有能量的积分,中子流量。使用中子活化分析发现测量的反应概率。该方法调整用户提供的试验频谱,其通常使用中子传输代码如蒙特卡罗n-颗粒计算。在目前现有的方法上观察到这种方法的益处包括:(a)与迭代展开方法相比,诸如在SIND-II代码中使用的迭代展开方法或在准确的先前频谱协方差时的方法中减少频谱形状的不切实异性伪影不可用; (b)降低的灵敏度,以增加衍生光谱的能量分辨率。本报告介绍了环形核心研究反应堆中央腔内各种光谱改变铲斗环境的调整结果。在每种情况下,将结果与使用LSL-M2产生的结果进行比较,这是一种常用于频谱调整的代码。遗传算法产生与LSL-M2产生的谱平均反应概率相当。作为遗传算法的一部分的先验频谱的局部段的拼接允许得到的频谱调节,以避免在未要求预先谱的情况下引入严重的窄能量宽度形状伪像。

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