首页> 外文会议>International topical meeting on nuclear reactor thermal hydraulics >UNCERTAINTY QUANTIFICATION OF TRACE WALL HEAT TRANSFER MODELING IN SUBCOOLED BOILING USING BFBT EXPERIMENTS
【24h】

UNCERTAINTY QUANTIFICATION OF TRACE WALL HEAT TRANSFER MODELING IN SUBCOOLED BOILING USING BFBT EXPERIMENTS

机译:使用BFBT实验的过冷沸腾道壁传热建模的不确定度量化。

获取原文

摘要

Forward quantification of uncertainties in code responses require knowledge of input model parameter uncertainties. Nuclear thermal-hydraulics codes such as RELAP5 and TRACE do not provide any information on physical model parameter uncertainties. A framework was developed to quantify input model parameter uncertainties using Maximum Likelihood Estimate (MLE) and Expectation-Maximization (E-M) algorithm for physical models using relevant experimental data. The objective of the present work is to perform the sensitivity analysis of the code input (physical model) parameters in TRACE and calculate their uncertainties using an MLE algorithm, with a particular focus on the subcooled boiling model, In this paper, the OECD/NEA BWR full-size fine-mesh bundle test (BFBT) data will be used to quantify selected physical model uncertainty of the TRACE code. The BFBT is based on a multi-rod assembly with measured data available for single or two-phase pressure drop, axial and radial void fraction distributions, and critical power for a wide range of systems conditions. In this study, the steady-state cross-sectional averaged void fraction distribution from BFBT experiments is used as the input for MLE algorithm, and selected physical model Probability Distribution Function (PDF) is the desired output quantity.
机译:代码响应中的不确定性的前向量化需要了解输入模型参数不确定性。 Relap5和Trace等核热液压码不提供有关物理模型参数不确定性的任何信息。开发了一种框架,以使用相关实验数据使用最大似然估计(MLE)和预期最大化(E-M)算法来量化输入模型参数不确定性。本作目前的目的是在跟踪中执行代码输入(物理模型)参数的敏感性分析,并使用MLE算法计算它们的不确定性,在本文中特别侧重于脱池沸腾模型,在本文中,OECD / NEA BWR全尺寸微网束测试(BFBT)数据将用于量化跟踪代码的选定的物理模型不确定性。 BFBT基于多杆组件,具有测量数据可用于单相或两相压降,轴向和径向空隙率分布,以及用于各种系统条件的临界功率。在该研究中,使用BFBT实验的稳态横截面平均空隙分数作为MLE算法的输入,并且选择的物理模型概率分布函数(PDF)是所需的输出量。

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