An open area of research for complex, cyber‐physical systems is how to adequately support decision making using reliability and failure data early in the systems engineering process. Having meaningful reliability and failure data available early offers information to decision makers at a point in the design process where decisions have a high impact to cost ratio. When applied to conceptual system design, widely used methods such as probabilistic risk analysis (PRA) and failure modes effects and criticality analysis (FMECA) are limited by the availability of data and often rely on detailed representations of the system. Further, existing methods for system reliability and failure methods have not addressed failure propagation in conceptual system design prior to selecting candidate architectures. Consideration given to failure propagation primarily focuses on the basic representation where failures propagate forward. In order to address the shortcomings of existing reliability and failure methods, this paper presents the function failure propagation potential methodology (FFPPM) to formalize the types of failure propagation and quantify failure propagation potential for complex, cyber‐physical systems during the conceptual stage of system design. Graph theory is leveraged to model and quantify the connectedness of the functional block diagram (FBD) to develop the metrics used in FFPPM. The FFPPM metrics include (i) the summation of the reachability matrix, (ii) the summation of the number of paths between nodes (i.e., functions) i and j for all i and j, and (iii) the degree and degree distribution. In plain English, these metrics quantify the reachability between functions in the graph, the number of paths between functions, and the connectedness of each node. The FFPPM metrics can then be used to make candidate architecture selection decisions and be used as early indicators for risk. The unique contribution of this research is to quantify failure propagation potential during conceptual system design of complex, cyber‐physical systems prior to selecting candidate architectures. FFPPM has been demonstrated using the example of an emergency core cooling system (ECCS) system in a pressurized water reactor (PWR).

中文翻译：

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图论方法在概念系统设计过程中预测功能故障的传播

复杂的网络物理系统的一个开放研究领域是如何在系统工程流程的早期阶段充分利用可靠性和故障数据来支持决策。尽早获得有意义的可靠性和故障数据，可以在设计过程中决策对成本比率产生重大影响的某个时刻为决策者提供信息。当应用于概念性系统设计时，广泛使用的方法（如概率风险分析（PRA）以及故障模式影响和严重性分析（FMECA））受到数据可用性的限制，并且通常依赖于系统的详细表示。此外，用于系统可靠性的现有方法和故障方法尚未在选择候选架构之前解决概念系统设计中的故障传播。对故障传播的考虑主要集中在故障向前传播的基本表示上。为了解决现有可靠性和故障方法的缺点，本文提出了功能故障传播潜能方法（FFPPM），用于对系统概念阶段复杂，网络物理系统的故障传播类型进行形式化和量化，以评估故障传播潜能。设计。利用图论对功能框图（FBD）的连通性进行建模和量化，以开发FFPPM中使用的度量。FFPPM指标包括（i）可达性矩阵的总和，（ii）节点之间的路径数（即功能）的总和 为了解决现有可靠性和故障方法的缺点，本文提出了功能故障传播潜能方法（FFPPM），用于对系统概念阶段复杂，网络物理系统的故障传播类型进行形式化和量化，以评估故障传播潜能。设计。利用图论对功能框图（FBD）的连通性进行建模和量化，以开发FFPPM中使用的度量。FFPPM指标包括（i）可达性矩阵的总和，（ii）节点之间的路径数（即功能）的总和 为了解决现有可靠性和故障方法的缺点，本文提出了功能故障传播潜能方法（FFPPM），用于对系统概念阶段复杂，网络物理系统的故障传播类型进行形式化和量化，以评估故障传播潜能。设计。利用图论对功能框图（FBD）的连通性进行建模和量化，以开发FFPPM中使用的度量。FFPPM指标包括（i）可达性矩阵的总和，（ii）节点之间的路径数（即功能）的总和 在系统设计的概念阶段的网络物理系统。利用图论对功能框图（FBD）的连通性进行建模和量化，以开发FFPPM中使用的度量。FFPPM指标包括（i）可达性矩阵的总和，（ii）节点之间的路径数（即功能）的总和 在系统设计的概念阶段的网络物理系统。利用图论对功能框图（FBD）的连通性进行建模和量化，以开发FFPPM中使用的度量。FFPPM指标包括（i）可达性矩阵的总和，（ii）节点之间的路径数（即功能）的总和i和j代表所有i和j，以及（iii）程度和程度分布。用简单的英语来说，这些指标量化了图中函数之间的可达性，函数之间的路径数以及每个节点的连通性。然后，可以将FFPPM度量标准用于做出候选体系结构选择决策，并用作风险的早期指标。这项研究的独特贡献是在选择候选架构之前，在复杂的网络物理系统的概念系统设计过程中量化故障传播的可能性。已使用压水堆（PWR）中的应急堆芯冷却系统（ECCS）系统的示例演示了FFPPM。