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A general framework for dependability modelling coupling discrete-event and time-driven simulation

机译:可依赖性建模耦合离散事件和时间驱动模拟的一般框架

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Analysis of complex failure scenarios and mitigation procedures of an industrial plant is one of the most important activity for the safety of the factory, the personnel and the surrounding areas. The dependability assessment of such systems is fulfilled by risk experts who, adopting well-known Reliability, Availability, Maintenance and Safety (RAMS) techniques, design and solve the stochastic failure model of the system. Traditional techniques like Fault Tree Analysis (FTA) or Reliability Block Diagrams (RBD) are of easy implementation but unrealistic, due to their simplified hypotheses that assume the components malfunction to be independent from each other and from the system working conditions.Dynamic Probabilistic Risk Assessment (DPRA) is the umbrella framework encompassing new mathematical and simulation formalisms aiming to relax the constraints of traditional techniques and increase the accuracy of dependability assessment. At the state of the art, DPRA cannot boast a well-defined methodology because the nature of a dynamic reliability problem can be so complex to require an ad-hoc modelling and resolution. Moreover, one of the main issues encountered by risk-practitioners is that there is a small support in terms of available tools or expert systems, specifically designed for DPRA problems.To tackle this lack, this paper presents the conception of general framework for the modelling and the simulation of a Stochastic Hybrid Fault Tree Automaton (SHyFTA), one of the most promising DPRA methodologies, able to combine Dynamic Fault Tree (DFT) with the deterministic model of the system process.The logic of the repairable DFT gates and the concepts for the implementation of a simulation engine combining Discrete Event Simulation (DES) and Time Driven Simulation (TDS) are illustrated and, a Matlab (R) toolbox library (SHyFTOO) has been coded and tested with a thorough validation campaign. Finally, a common case study in industrial engineering has been modelled and analysed under different stand-by configurations in order to demonstrate the modelling flexibility of the toolbox.
机译:工业厂的复杂失败情景和缓解程序分析是工厂安全,人员和周边地区的最重要活动之一。这种系统的可靠性评估由风险专家满足,采用众所周知的可靠性,可用性,维护和安全(RAMS)技术,设计和解决系统随机故障模型。传统技术,如故障树分析(FTA)或可靠性框图(RBD)具有易于实现而不实现的,但由于其简化的假设,该假设假设组件故障彼此独立,并且从系统工作条件较独立。动态概率风险评估(DPRA)是包括新的数学和模拟形式主义的伞形框架,其旨在放宽传统技术的约束,提高可靠性评估的准确性。在现有技术中,DPRA不能夸张定义明确的方法,因为动态可靠性问题的性质可能是如此复杂的,以便需要临时建模和分辨率。此外,风险从业者遇到的主要问题之一是,在可用的工具或专家系统方面存在小的支持,专门为DPRA问题设计。解决这种缺乏,本文提出了造型框架的概念以及STOCHAST混合故障树自动化(SHYFTA)的仿真,最有前途的DPRA方法之一,能够将动态故障树(DFT)与系统过程的确定性模型相结合。可修复的DFT门和概念的逻辑为了实现组合离散事件仿真(DES)和时间驱动模拟(TDS)的模拟引擎的实现,并且,MATLAB(R)工具箱库(SHYFTOO)已被编码和测试,并通过彻底的验证广告系列进行测试。最后,在不同的待机配置下进行了建模和分析了工业工程的常见案例研究,以证明工具箱的建模灵活性。

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