论文标题
使用贝叶斯网络的预测能力成熟度定量
Predictive Capability Maturity Quantification using Bayesian Network
论文作者
论文摘要
在核工程中，建模和仿真（M＆SS）广泛用于支持风险信息的安全分析。由于核安全分析具有重要的含义，因此需要一个令人信服的验证过程来评估模拟充分性，即M＆S工具可以充分代表感兴趣的系统量的程度。但是，由于数据差距，验证成为不确定性下的决策过程。需要专业知识和判断才能收集，选择，表征和整合证据，以实现最终的充分性决定。但是，在验证框架中，CSAU：代码缩放，适用性和不确定性（NUREG/CR-5249）和EMDAP：评估模型开发和评估过程（RG 1.203），这种决策过程在很大程度上是隐式的和晦涩的。当场景很复杂时，知识偏见和不可靠的判断可能会被忽略，这可能会增加模拟充分性结果和相应风险的不确定性。因此，需要一个框架来以实用，透明和一致的方式形式化模拟充分性的决策过程。本文提出了一个框架“使用贝叶斯网络（PCMQBN）的预测能力成熟度定量”，作为基于验证活动收集的信息评估模拟充分性的量化框架。准备了一个案例研究，以评估平滑颗粒流体动力学模拟在外部洪水场景中预测流体动力学上静态结构上的足够性。与定性和隐性的充分性评估相比，PCMQBN能够提高对仿真足够结果的信心，并减少风险知名安全性分析中的预期损失。
In nuclear engineering, modeling and simulations (M&Ss) are widely applied to support risk-informed safety analysis. Since nuclear safety analysis has important implications, a convincing validation process is needed to assess simulation adequacy, i.e., the degree to which M&S tools can adequately represent the system quantities of interest. However, due to data gaps, validation becomes a decision-making process under uncertainties. Expert knowledge and judgments are required to collect, choose, characterize, and integrate evidence toward the final adequacy decision. However, in validation frameworks CSAU: Code Scaling, Applicability, and Uncertainty (NUREG/CR-5249) and EMDAP: Evaluation Model Development and Assessment Process (RG 1.203), such a decision-making process is largely implicit and obscure. When scenarios are complex, knowledge biases and unreliable judgments can be overlooked, which could increase uncertainty in the simulation adequacy result and the corresponding risks. Therefore, a framework is required to formalize the decision-making process for simulation adequacy in a practical, transparent, and consistent manner. This paper suggests a framework "Predictive Capability Maturity Quantification using Bayesian network (PCMQBN)" as a quantified framework for assessing simulation adequacy based on information collected from validation activities. A case study is prepared for evaluating the adequacy of a Smoothed Particle Hydrodynamic simulation in predicting the hydrodynamic forces onto static structures during an external flooding scenario. Comparing to the qualitative and implicit adequacy assessment, PCMQBN is able to improve confidence in the simulation adequacy result and to reduce expected loss in the risk-informed safety analysis.
