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Automatic generation of generalized event sequence diagrams for guiding simulation based dynamic probabilistic risk assessment of complex systems.

机译：自动生成通用事件序列图，以指导基于仿真的复杂系统的动态概率风险评估。

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Dynamic probabilistic risk assessment (DPRA) is a systematic and comprehensive methodology that has been used and refined over the past two decades to evaluate the risks associated with complex systems such as nuclear power plants, space missions, chemical plants, and military systems. A critical step in DPRA is generating risk scenarios which are used to enumerate and assess the probability of different outcomes. The classical approach to generating risk scenarios is not, however, sufficient to deal with the complexity of the above-mentioned systems.;The primary contribution of this dissertation is in offering a new method for capturing different types of engineering knowledge and using them to automatically generate risk scenarios, presented in the form of generalized event sequence diagrams, for dynamic systems. This new method, as well as several important applications, is described in detail. The most important application is within a new framework for DPRA in which the risk simulation environment is guided to explore more interesting scenarios such as low-probability/high-consequence scenarios. Another application considered is the use of the method to enhance the process of risk-based design.

机译：动态概率风险评估（DPRA）是一种系统，全面的方法，在过去的二十年中一直使用和完善该方法，以评估与复杂系统（如核电站，太空任务，化工厂和军事系统）相关的风险。 DPRA中的关键一步是生成风险情景，这些风险情景用于枚举和评估不同结果的可能性。然而，经典的生成风险情景的方法不足以解决上述系统的复杂性。本论文的主要贡献在于提供了一种捕获不同类型的工程知识并自动使用它们的新方法。生成针对动态系统的风险情景，以通用事件序列图的形式表示。详细介绍了此新方法以及一些重要的应用程序。最重要的应用是在DPRA的新框架内，其中指导风险模拟环境探索更有趣的场景，例如低概率/高后果场景。考虑的另一个应用是使用该方法来增强基于风险的设计过程。

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作者
Nejad-Hosseinian, Seyed Hamed.;
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University of Maryland, College Park.;

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授予单位 University of Maryland, College Park.;
学科 Engineering General.;Engineering System Science.;Engineering Robotics.
学位 Ph.D.
年度 2007
页码 158 p.
总页数 158
原文格式 PDF
正文语种 eng
中图分类工程基础科学;系统科学;
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专利

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Automatic generation of generalized event sequence diagrams for guiding simulation based dynamic probabilistic risk assessment of complex systems.

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