数据同化重建中子活度场测量网的优化设计
Optimal design of measurement network for neutronic activity field reconstruction by data assimilation
摘要：
利用数据同化框架，融合模型和测量信息，可以确定核反应堆堆芯中子活动场的最佳重建。在本文中，我们专注于解决反问题，确定一个最佳的重新分配的核心内的测量仪器，得到最好的结果，从数据同化重建过程。位置优化是利用模拟退火算法实现的，基于Metropolis-Hastings算法。此外，为了解决优化计算的挑战，数据同化的代数改进已经开发，并在这里提出。
英文摘要：
Using data assimilation framework, to merge information from model and measurement, an optimal reconstruction of the neutronic activity field can be determined for a nuclear reactor core. In this paper, we focus on solving the inverse problem of determining an optimal repartition of the measuring instruments within the core, to get the best possible results from the data assimilation reconstruction procedure. The position optimisation is realised using Simulated Annealing algorithm, based on the Metropolis-Hastings one. Moreover, in order to address the optimisation computing challenge, algebraic improvements of data assimilation have been developed and are presented here.
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