首页> 外文期刊>Reliability Engineering & System Safety >Functional failure analysis of a thermal-hydraulic passive system by means of Line Sampling
【24h】

Functional failure analysis of a thermal-hydraulic passive system by means of Line Sampling

机译:通过线采样分析热工无源系统的功能故障

获取原文
获取原文并翻译 | 示例
           

摘要

Assessing the failure probability of a thermal-hydraulic (T-H) passive system amounts to evaluating the uncertainties in its performance. Two different sources of uncertainties are usually considered: randomness due to inherent variability in the system behavior (aleatory uncertainty) and imprecision due to lack of knowledge and information on the system (epistemic uncertainty).rnIn this paper, we are concerned with the epistemic uncertainties affecting the model of a T-H passive system and the numerical values of its parameters. Due to these uncertainties, the system may find itself in working conditions that do not allow it to accomplish its functions as required. The estimation of the probability of these functional failures can be done by Monte Carlo (MC) sampling of the epistemic uncertainties affecting the model and its parameters, followed by the computation of the system function response by a mechanistic T-H code.rnEfficient sampling methods are needed for achieving accurate estimates, with reasonable computational efforts. In this respect, the recently developed Line Sampling (LS) method is here considered for improving the MC sampling efficiency. The method, originally developed to solve high-dimensional structural reliability problems, employs lines instead of random points in order to probe the failure domain of interest. An "important direction" is determined, which points towards the failure domain of interest; the high-dimensional reliability problem is then reduced to a number of conditional one-dimensional problems which are solved along the "important direction". This allows to significantly reduce the variance of the failure probability estimator, with respect to standard random sampling.rnThe efficiency of the method is demonstrated by comparison to the commonly adopted Latin Hypercube Sampling (LHS) and first-order reliability method (FORM) in an application of functional failure analysis of a passive decay heat removal system in a gas-cooled fast reactor (GFR) of literature.
机译:评估热工(T-H)被动系统的故障概率等于评估其性能的不确定性。通常考虑两种不同的不确定性来源:由于系统行为固有的可变性(随机不确定性)和由于缺乏系统知识和信息而引起的不精确性(认知不确定性)。rn在本文中,我们关注的是认知不确定性影响TH无源系统的模型及其参数的数值。由于这些不确定性,系统可能会发现自己处于无法使其按要求完成功能的工作状态。通过对影响模型及其参数的认知不确定性进行蒙特卡洛(MC)采样,然后通过机械TH代码计算系统功能响应,可以估算出这些功能失效的可能性.rn需要有效的采样方法通过合理的计算工作来获得准确的估算值。在这方面,这里考虑使用最近开发的线采样(LS)方法来提高MC采样效率。该方法最初是为解决高维结构可靠性问题而开发的,它采用线代替随机点来探测感兴趣的失效域。确定了“重要方向”,该方向指向所关注的故障域。然后,将高维可靠性问题简化为沿“重要方向”解决的许多条件一维问题。与标准随机抽样相比,这可以显着降低故障概率估计量的方差。rn通过与常用的拉丁超立方体抽样(LHS)和一阶可靠性方法(FORM)进行比较,证明了该方法的效率。被动衰减式除热系统功能失效分析在气冷快堆中的应用

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