【作者】 尹三井；

【导师】 彭敏俊；

【作者基本信息】 哈尔滨工程大学 ， 核能科学与工程， 2008， 硕士

【摘要】 概率风险评价(Probabilistic Risk Assessment简称PRA)是一个确保系统安全的分析过程。随着动态系统的规模和硬件、软件及人因之间相互作用的复杂程度日益增加,由传统PRA方法列举风险假想存在着极大的难度。在过去15年里,很多动态概率风险评价(Dynamic Probabilistic Risk Assessment简称DPRA)方法已作为辅助手段,用于处理大型复杂动态系统。本文在对DPRA常用方法研究的基础上提出基于制导策略的DPRA框架,即通过工程认识来指导仿真,由此进一步提高效率、获取更高的精度。工程认识体现在计划程序上,将生成的计划作为蓝图指导仿真；调度程序通过控制时间和随机事件来指导仿真。仿真期间,随机事件在支点处被载入调度程序,由调度程序决定是否予以仿真,调度程序原则上偏重更有价值的事件。载入事件的价值取决于研究过程中获取的信息增益及重要度。获取信息的价值由平均信息量来衡量、重要度则是基于对该工程的判断及认识。仿真结果将在运行中记录并归类。计划程序从仿真结果中获取经验数据并升级,继续指导下一步仿真。为实现基于制导策略的DPRA框架,本文开发了DPRAP(Probabilistic Risk Assessment Platform)。该软件平台包括友好的人机界面,设有DPRA模型数据库,用以辅助建立仿真模型。将工程认识载入计划程序中,可自动生成计划；随后调度程序将根据制定的计划指导仿真。通过仿真生成事故事件序列,从而估算出系统末状态的失效概率。更多还原

【Abstract】 Probabilistic risk assessment (PRA) is a systematic process of examining how engineered systems work to ensure safety. With the growth of the size of the dynamic systems and the complexity of the interactions between hardware, software, and humans, it is extremely difficult to enumerate the risky scenarios by the traditional PRA methods. Over the past 15 years, a host of DPRA methods have been proposed to serve as supplemental tools to traditional PRA to deal with complex dynamic systems.A new dynamic probabilistic risk assessment framework is proposed in this dissertation. In this framework a new exploration strategy is employed. The engineering knowledge of the system is explicitly used to guide the simulation to achieve higher efficiency and accuracy. The engineering knowledge is reflected in the "Planner" which is responsible for generating plans as a high level map to guide the simulation. A scheduler is responsible for guiding the simulation by controlling the timing and occurrence of the random events. During the simulation the possible random events are proposed to the scheduler at branch points. The scheduler decides which events are to be simulated. Scheduler would favor the events with higher values. The value of a proposed event depends on the information gain from exploring that scenario, and the importance factor of the scenario. The information gain is measured by the information entropy, and the importance factor is based on the engineering judgment. The simulation results are recorded and grouped for later studies. The planner may "learn" from the simulation results, and update the plan to guide further simulation.DPRAP(Dynamic Probabilistic Risk Assessment Platform) is the software package which implements the new methodology. It provides the users with a friendly interface and a rich DPRA library to aid in the construction of the simulation mode. The engineering knowledge can be input into the Planner, which would generate a plan automatically. The scheduler would guide the simulation according to the plan. The simulation generates many accident event sequences and estimates of the end state probabilities.更多还原