首页> 外文会议>European Safety and Reliability Conference >Uncertainty analysis for the predicted proportion of fuel rods failed during a hypothetical loss of coolant accident
【24h】

Uncertainty analysis for the predicted proportion of fuel rods failed during a hypothetical loss of coolant accident

机译:预测比例的燃料棒的不确定分析失败了在诊断的冷却剂事故中失败

获取原文
获取外文期刊封面目录资料

摘要

One of the requirements in Germain licensing processes for pressurized water reactors (PWRs) is that the core damage extent must not exceed 10% in case of a hypothetical loss of coolant accident (LOCA). The core damage extent is the proportion P of fuel rods in the core bursting during the accident. Mainly two computer codes are applied to predict P: a thermal-hydraulics code and a fuel rod code evaluating the fuel rod behaviour under LOCA-thermal-hydraulics. This paper presents an approach to an uncertainty analysis for P based on the Monte Carlo technique. Prime intention of the analysis is to account for the numerous epistemic uncertainties involved in the calculation of P. To reduce the computational effort, the analysis is performed on the basis of a random sample of fuel rods. Thus, also the uncertainty in P due to the inference from only a sample from the core has to be taken into account. The Bayesian approach is used to describe the overall uncertainty in P. Uncertainty statements are derived from a random sample from the average posterior distribution of P. For comparison, also a frequentist approach based on an upper 95%-confidence limit is considered. Results from an illustrative uncertainty analysis are presented.
机译:用于加压水反应器(PWR)的Germain许可方法的要求之一是,如果有一个假设的冷却剂事故(LOCA)的情况下,核心损坏程度不得超过10%。核心损伤程度是事故期间核心爆裂中的燃料棒的比例P.主要应用两台计算机代码来预测P:热液压码和燃料杆代码,评估基因液下的燃料杆行为。本文介绍了基于蒙特卡罗技术对P的不确定性分析的方法。分析的主要意图是考虑到P的计算中涉及的许多认知不确定性。为了减少计算工作,基于燃料棒的随机样品进行分析。因此,必须考虑来自仅来自来自核心的样品的推断的P中的不确定性。贝叶斯方法用于描述P. P.不确定陈述的总不确定性来自来自P的平均后剖分布的随机样品。对于比较,考虑基于95%的较高的95%的频率方法。提出了说明性不确定性分析的结果。

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