Analysis of Common Cause Failure Data in Nuclear Power Plant Safety Assessment

该补助金支持开发新的统计方法，用于分析复杂系统（如核电厂组件组）的共因故障数据。 为了模拟共因故障的目的，研究可以导致二项式故障率混合模型的发展，基于参数冲击模型开发的电厂风险评估。 除了这个混合模型估计，将追求各种结果，包括非参数和参数估计;置信带和其他措施的不确定性;一般解决方案的系统不相同的组件;和相关的限制属性。混合模型将作为一个出发点，进一步研究统计分析的基础上相关的故障模型。本研究还探讨了技术的映射，以取代缺失的数据与估计的数据在风险评估，并将有助于表征的不确定性与各种模型用于映射过程中使用统计理论，除了蒙特卡洛模拟。 最初的二项失效率模型受到了批评，因为许多现有的数据库的模型拟合较差。 本研究中的实际推广比原始模型或其非参数替代方案更复杂，但模型拟合可以大大提高。在工程文献中有很强的定性分析基础（筛选分析、故障树分析等），但对共因失效研究的定量方面缺乏指导。 如果成功，这项研究将有助于 核安全领域的定量风险分析。

This grant supports the development of new statistical methods for analyzing common cause failure data for complex systems, such as nuclear power plant component groups. For the purpose of modeling common cause failures, the research can lead to the development of a binomial failure rate mixture model, based on a parametric shock model developed for power plant risk assessment. Beyond this mixture model estimator, various results will be pursued, including both non-parametric and parametric estimators; confidence bands and other measures of uncertainty; general solutions for systems of non identical components; and, pertinent limit properties. The mixture model will serve as a point of departure to further research into statistical analyses based on dependent failure models. This research also investigates techniques of mapping that replace missing data with estimated data in the risk assessment, and will help to characterize the uncertainty involved with various models used for the mapping procedure using statistical theory in addition to Monte Carlo simulation. The original binomial failure rate model has been criticized due to the many existing databases for which the model fit is poor. The realistic generalization in this investigation is more complex than the original model or its non-parametric alternatives, but model fit can be greatly improved. There exists a strong foundation of qualitative analysis in the engineering literature (screening analysis, fault tree analysis, etc.), but little guidance with respect to some quantitative aspects common cause failure research. If successful, this research will contribute to quantitative risk analyses in the nuclear safety field.