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Parallel fault tree analysis for accurate reliability of complex systems

机译:并行故障树分析可确保复杂系统的准确可靠性

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Fault tree analysis is one of the methods for the probabilistic risk assessment of components and subsystems of nuclear power plants. The algorithms that solve a fault tree have been until now serial. Instead, this study presents new algorithms that handle and solve a fault tree by taking advantage of the new state of the art in parallel computing: general purpose graphic processor unit (GPGPU). The subsystems of nuclear power plants are the target of this study. However, the method can be used on many others, complex, engineering systems. The different, developed, parallel algorithms are: one builder, which assembles the topology matrix of the fault tree and leads the computation of the three, developed, new solvers. A bottom-up solver, a cut sets solver, and a Monte Carlo simulation solver. The probability of the top event, and the probabilities of each cut sets are computed. The results shows that, given the same investment, a GPU can handle larger fault trees than a CPU implementation. The developed solvers are the foundation of the next generation parallel algorithms for the tree-based analysis of complex systems. (C) 2017 Elsevier Ltd. All rights reserved.
机译:故障树分析是核电厂组件和子系统的概率风险评估方法之一。迄今为止,解决故障树的算法一直是串行的。取而代之的是,这项研究提出了一种利用并行计算的最新技术来处理和解决故障树的新算法:通用图形处理器单元(GPGPU)。核电厂的子系统是本研究的目标。但是,该方法可以在许多其他复杂的工程系统上使用。不同的,已开发的并行算法是:一个构建器,该构建器组装故障树的拓扑矩阵,并负责计算三个已开发的新求解器。自底向上求解器,割集求解器和蒙特卡洛模拟求解器。计算最高事件的概率以及每个割集的概率。结果表明,在相同的投入下,GPU可以处理比CPU实现更大的故障树。所开发的求解器是用于基于树的复杂系统分析的下一代并行算法的基础。 (C)2017 Elsevier Ltd.保留所有权利。

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