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Supporting systems of systems hazard analysis using multi-agent simulation

机译:使用多主体仿真的系统危害分析支持系统

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When engineers create a safety-critical system, they need to perform an adequate hazard analysis. For Systems of Systems (SoSs), however, hazard analysis is difficult because of the complexity of SoS and the environments they inhabit. Traditional hazard analysis techniques often rely upon static models of component interaction and have difficulties exploring the effects of multiple coincident failures. They cannot be relied on, therefore, to provide adequate hazard analysis of SoS. This paper presents a hazard analysis technique (SimHAZAN) that uses multi-agent modelling and simulation to explore the effects of deviant node behaviour within a SoS. It defines a systematic process for developing multi-agent models of SoS, starting from existing models in the MODAF architecture framework and proceeding to implemented simulation models. It then describes a process for running these simulations in an exploratory way, bounded by estimated probability. This process generates extensive logs of simulated events; in order to extract the causes of accidents from these logs, this paper presents a tool-supported analysis technique that uses machine learning and agent behaviour tracing. The approach is evaluated by comparison to some explicit requirements for SoS hazard analysis, and by applying it to a case study. Based on the case study, it appears that SimHAZAN has the potential to reveal hazards that are difficult to discover when using traditional techniques.
机译:工程师创建安全关键型系统时,需要执行足够的危害分析。但是,对于系统系统(SoS),由于SoS的复杂性及其所处的环境,因此危害分析非常困难。传统的危害分析技术通常依赖于组件交互的静态模型,并且难以探究多个同时发生的故障的影响。因此,不能依靠它们来提供足够的SoS危害分析。本文提出了一种危害​​分析技术(SimHAZAN),该技术使用多主体建模和仿真来探索SoS中异常节点行为的影响。它定义了用于开发SoS的多代理模型的系统过程,该过程从MODAF体系结构框架中的现有模型开始,然后进行到已实现的仿真模型。然后,它描述了一种以探索性方式运行这些模拟的过程,并以估计的概率为边界。该过程生成大量模拟事件日志;为了从这些日志中提取事故原因,本文提出了一种工具支持的分析技术,该技术使用了机器学习和代理行为跟踪。通过与SoS危害分析的一些明确要求进行比较,并将其应用于案例研究,对该方法进行了评估。根据案例研究,SimHAZAN似乎有潜力揭示使用传统技术难以发现的危害。

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