论文标题
保护系统功效分析的概率量化注释：随机动力学，信息流和启动事件到达时间
A Note on Probability Quantification for Protective System Efficacy Analysis: Stochastic Dynamics, Information Flow, and Initiating Event Arrival Times
论文作者
论文摘要
概率量化（PQ）对安全 - 关键保护系统功效的预测具有挑战性。然而，PQ方法论的普及（例如，概率风险评估（PRA），定量风险分析（QRA）和概率安全分析（PSA）（PSA））正在增长，现在可以将其写入监管规则中。预测建模中的PQ由于其概率理论的基础而具有吸引力。但是，某些重要的与安全有关的事件不是概率测量的，这对于依赖PQ计算的风险分析方法是有问题的。在此，我们确定了为什么可用信息的动态在管理PQ的忠诚度中起着至关重要的作用，以及为什么PQ在分析安全关键保护系统中受到某些关键事件的不可估量的限制。我们提供了一个历史例子，为我们的观察提供了实用的背景。最后，我们讨论了可衡量性对法规决策的含义，该核工业立法倡导增加对风险知情的，基于绩效的高级反应器许可的法规的使用。
Probability Quantification (PQ) predictions of the efficacy of safety-critical protective systems is challenging. Yet, the popularity of PQ methodologies (e.g., Probabilistic Risk Assessment (PRA), Quantitative Risk Analysis (QRA) and Probabilistic Safety Analysis (PSA)) is growing and can now be found written into regulatory rules. PQ in predictive modeling is attractive because of its grounding in probability theory. But, certain important safety related events are not probability-measurable which is problematic for risk-analytic methodologies that rely on PQ computations. Herein, we identify why the dynamics of available information play an essential role in governing the fidelity of PQ, and why PQ in the analysis of safety-critical protective systems is limited by the un-measurability of certain critical events. We provide an historical example that provides a practical context for our observations. Finally we discuss the implications of measurability for regulatory decision-making governed by recent nuclear industry legislation advocating increased use of risk informed, performance-based regulation for advanced reactor licensing.
