论文标题
迭代贝叶斯蒙特卡洛进行核数据评估
Iterative Bayesian Monte Carlo for nuclear data evaluation
论文作者
论文摘要
在这项工作中，我们探讨了迭代性贝叶斯蒙特卡洛（IBM）程序在评估的核数据库（TERTL）框架内进行核数据评估。为了识别复制所选实验数据的模型和参数组合，在TALYS代码中实现的不同物理模型进行了采样并同时进行了变化，以生成具有唯一模型组合的随机输入文件。所有考虑的模型都被认为是先验的。然后，使用TALYS代码系统同时使用这些模型的参数来生成一组随机ENDF文件，这些文件被处理到X-Y表中，以与贝叶斯框架内的EXFOR数据库中选定的实验数据进行比较。为了改善我们对实验数据的拟合，我们通过重新采样模型参数围绕此文件而迭代更新我们的“最佳”文件 - 最大化似然函数的文件。提出的方法已用于评估1-100 MEV入射能区域之间的P+CD-111和CO-59。最后，将调整后的文件与EXFOR数据库的实验数据以及Terdl-2017和Jendl-4.0/HE核数据库的评估进行了比较。
In this work, we explore the use of an iterative Bayesian Monte Carlo (IBM) procedure for nuclear data evaluation within a Talys Evaluated Nuclear data Library (TENDL) framework. In order to identify the model and parameter combinations that reproduce selected experimental data, different physical models implemented within the TALYS code, were sampled and varied simultaneously to produce random input files with unique model combinations. All the models considered were assumed to be equal a priori. Parameters to these models were then varied simultaneously using the TALYS code system to produce a set of random ENDF files which were processed into x-y tables for comparison with selected experimental data from the EXFOR database within a Bayesian framework. To improve our fit to experimental data, we iteratively update our 'best' file - the file that maximises the likelihood function - by re-sampling model parameters around this file. The method proposed has been applied for the evaluation of p+Cd-111 and Co-59 between 1 - 100 MeV incident energy region. Finally, the adjusted files were compared with experimental data from the EXFOR database as well as with evaluations from the TENDL-2017 and JENDL-4.0/HE nuclear data libraries.
