• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Risk analysis >An Adaptive Simulation Framework for the Exploration of Extreme and Unexpected Events in Dynamic Engineered Systems
【24h】

An Adaptive Simulation Framework for the Exploration of Extreme and Unexpected Events in Dynamic Engineered Systems

机译：探索动态工程系统中极端事件和意外事件的自适应仿真框架

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The end states reached by an engineered system during an accident scenario depend not only on the sequences of the events composing the scenario, but also on their timing and magnitudes. Including these additional features within an overarching framework can render the analysis infeasible in practical cases, due to the high dimension of the system state-space and the computational effort correspondingly needed to explore the possible system evolutions in search of the interesting (and very rare) ones of failure. To tackle this hurdle, in this article we introduce a framework for efficiently probing the space of event sequences of a dynamic system by means of a guided Monte Carlo simulation. Such framework is semi-automatic and allows embedding the analyst's prior knowledge about the system and his/her objectives of analysis. Specifically, the framework allows adaptively and intelligently allocating the simulation efforts preferably on those sequences leading to outcomes of interest for the objectives of the analysis, e.g., typically those that are more safety-critical (and/or rare). The emerging diversification in the filling of the state-space by the preference-guided exploration allows also the retrieval of critical system features, which can be useful to analysts and designers for taking appropriate means of prevention and mitigation of dangerous and/or unexpected consequences. A dynamic system for gas transmission is considered as a case study to demonstrate the application of the method.
机译：在事故场景中，工程系统达到的最终状态不仅取决于构成场景的事件的顺序，还取决于事件的时间和大小。由于系统状态空间的高维以及为寻找有趣的（而且非常罕见）的系统可能需要的计算工作，在实际情况下，将这些附加功能包括在总体框架中会使分析不可行。失败的。为了解决这一难题，在本文中，我们介绍了一个框架，该框架通过引导式蒙特卡洛模拟有效地探测动态系统的事件序列空间。这种框架是半自动的，可以嵌入分析师对系统及其分析目标的先验知识。具体地，该框架允许自适应地和智能地优选地对导致针对分析目标感兴趣的结果的那些序列（例如，通常对安全性要求更高（和/或罕见）的那些序列）进行自适应分配。通过偏好引导的探索在状态空间填充中出现的新的多样化也允许检索关键的系统特征，这对于分析人员和设计人员采取适当的预防和减轻危险和/或意想不到的后果的手段可能是有用的。以气体传输动态系统为案例研究，以证明该方法的应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号