Abstract

The structural integrity of a reactor pressure vessel (RPV) is a crucial issue for an operating nuclear power plant, especially in the beltline region, which suffers the highest neutron irradiation. Owing to its capability of considering parameters based on statistical distributions and provision of objective risk-informed results, the probabilistic fracture mechanics (PFM) method is widely used in evaluating the structural integrity of RPVs. However, the flaw characteristics used for PFM analysis are mainly derived from particular vessel inspection information such as from the Pressure Vessel Research User Facility and Shoreham vessels, which may not be able to truly represent the vessel-specific condition of an analyzed RPV. In this work, the Bayesian inference, which combines prior flaw data with new inspection results as well as uncertainties, is used to develop posterior vessel-specific flaw distributions. Then, the updated flaw model is used for PFM analysis to investigate the effects on the fracture probability assessment of RPVs subjected to pressurized thermal shocks (PTSs). Considering the updated flaws based on the inspection data, the PFM analysis result could be more realistic to predict the fracture risks of RPVs during operation.

摘要

反应堆压力容器（RPV）的结构完整性对于正在运行的核电站，尤其是在遭受中子辐射最高的腰线地区的核电站而言，是至关重要的问题。由于其能够基于统计分布来考虑参数并提供客观的风险相关结果，因此概率断裂力学（PFM）方法被广泛用于评估RPV的结构完整性。但是，用于PFM分析的缺陷特征主要来自特定的容器检查信息，例如来自压力容器研究用户设施和Shoreham容器，这些信息可能无法真正代表所分析RPV的特定于容器的状况。在这项工作中，贝叶斯推理将先前的缺陷数据与新的检查结果以及不确定性结合在一起，用于开发特定于后血管的缺陷分布。然后，将更新后的缺陷模型用于PFM分析，以研究对承受加压热冲击（PTS）的RPV的断裂概率评估的影响。考虑到基于检查数据的更新缺陷，PFM分析结果可以更实际地预测RPV在操作过程中的破裂风险。