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Safety management in NPPs using an evolutionary algorithm technique

机译:使用进化算法技术的核电厂安全管理

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摘要

The general goal of safety management in Nuclear Power Plants (NPPs) is to make requirements and activities more risk effective and less costly. The technical specification and maintenance (TS&M) activities in a plant are associated with controlling risk or with satisfying requirements, and are candidates to be evaluated for their resource effectiveness in risk-informed applications. Accordingly, the risk-based analysis of technical specification (RBTS) is being considered in evaluating current TS. The multi-objective optimization of the TS&M requirements of a NPP based on risk and cost, gives the pareto-optimal solutions, from which the utility can pick its decision variables suiting its interest. In this paper, a multi-objective evolutionary algorithm technique has been used to make a trade-off between risk and cost both at the system level and at the plant level for loss of coolant accident (LOCA) and main steam line break (MSLB) as initiating events.
机译:核电厂(NPP)的安全管理的总体目标是使需求和活动具有更高的风险有效性和更低的成本。工厂中的技术规范和维护(TS&M)活动与控制风险或满足要求相关联,并且是在风险告知应用程序中评估其资源有效性的候选对象。因此,在评估当前技术支持时,正在考虑基于风险的技术规范分析(RBTS)。基于风险和成本的NPP TS&M需求的多目标优化,给出了最优的解决方案,公用事业公司可以从中选择适合其兴趣的决策变量。在本文中,多目标进化算法技术已被用于在系统级和工厂级的风险和成本之间进行权衡,以弥补冷却剂事故(LOCA)和主蒸汽管线中断(MSLB)的损失。作为发起事件。

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