Sensitivity Analysis of Key Parameters for Dynamical Analysis of Reactor Coolant System
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摘要: 反应堆冷却剂系统(RCS)在极端事故工况下的动力响应计算是评估核电厂安全的重要技术手段。定量考察系统结构的关键参数对系统动力响应的敏感性,是可靠评价系统响应的重要方面。本文通过全局敏感性和相关性分析,对一种堆型蒸汽发生器(SG)支承刚度对地震条件下主系统载荷分配的敏感性进行了研究。研究表明,支承刚度对SG局部范围内主系统载荷分配影响度较高,对距离较远的反应堆压力容器影响度较低。此外,还建立了描述关键参数到载荷分配的输入输出关系,并通过神经网络对输入输出关系进行了回归建模。该神经网络模型能够快速准确地对发生支承结构设计变更后的主系统地震载荷分配进行评估。
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关键词:
- 反应堆冷却剂系统(RCS) /
- 参数敏感性分析 /
- 复杂模型 /
- 力学评定 /
- 神经网络
Abstract: Dynamical analysis of reactor coolant system(RCS) under extreme accidents is a key technical approach for nuclear power plant safety assessment. Quantitative examination of the sensitivity of key RCS structural parameters against system dynamical responses is a crucial aspect for the reliable evaluation of RCS responses. This paper presents a sensitivity analysis of steam generator(SG) support stiffness against the RCS load distribution under seismic load by means of global sensitivity analysis and correlation analysis. It is shown that SG support stiffness is more influential to load distributions at local scale, namely, close to SG, and less influential to the load distribution of distant reactor pressure vessel(RPV). Moreover, the input-output relationship that characterizes the mapping from key parameters to RCS load distributions is constructed and a regression model via artificial neural network(ANN) is built. The ANN model enables the fast and accurate estimation of RCS load distribution upon structural design modifications of SG supports. -
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