堆芯功率分布重构的两种空间统计性算法

本工作提出两种基于空间统计性理论的堆芯功率分布重构算法：普通克里金方法是一种基于空间自协方差的最优插值法；卡尔曼滤波方法是一种有效结合理论计算与测量数据的数据同化方法。应用秦山第二核电厂3号机组和大亚湾核电站1号机组的测量数据对上述两种方法的功率分布重构精度进行了验证，并与耦合系数法（CECOR）的重构精度进行了比较。结果表明，两种方法的重构误差均满足工程要求，且重构精度优于耦合系数法。

Two Spatial Statistical Algorithms for Core Power Distribution Reconstruction

Two core power distribution reconstruction methods based on spatial statistical theory were proposed. Ordinary Kriging method is an optimal interpolation method based on spatial autocovariance and Kalman filter method is one of the data assimilation methods which could combine theoretical computation and measurements effectively. Measurement data from Unit 3 reactor of Qinshan No.2 Nuclear Power Plant and Unit 1 reactor of Daya Bay Nuclear Power Plant were used to verify the accuracy of these methods, and comparisons were made between these methods and the coupling coefficients method. The results show that the reconstruction errors of two methods satisfy the requirement of engineering and the reconstruction accuracies of two methods are better than the coupling coefficients method.