Structural integrity assessment of CANDU pressure tubes using Sobol indices for global sensitivity analysis

被引:1
|
作者
Pelayo, R. E. Ortega [1 ]
El Bouzidi, S. [1 ]
Trottier, A. [1 ]
Forgues, F. [1 ]
Pfeiffer, S. [1 ]
机构
[1] Canadian Nucl Labs Ltd, 286 Plant Rd, Chalk River, ON K0J 1J0, Canada
关键词
CANDU pressure tubes; Structural integrity; Leak-before-break; Global sensitivity analysis; Sobol method; LEAK-BEFORE-BREAK; DHC INITIATION; OPTIMIZATION; TREE;
D O I
10.1016/j.nucengdes.2024.113499
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
CANDU1 1 reactors are a channel-type design where up to 480 zirconium alloy pressure tubes (PTs) act as the reactor pressure boundary. Fitness-for-service standards such as CSA N285.8 (CSA Group, 2015) have been established to prescribe the requirements of pressure tube evaluations to maintain their integrity throughout their lifetime. Probabilistic leak-before-break (LBB) assessments can be used in evaluations to demonstrate that the likelihood of a flaw growing past the stability point while undetected (or before a safe shutdown can be achieved) is below regulatory limits. The assessments typically require a ranking of model parameters based on their influence. The ranking process traditionally uses expert judgment and local sensitivity analysis methods. There has been recent interest in implementing global methods for LBB assessments as they can manage large numbers of variables and extensive sampling spaces. However, their adoption is hindered by the computational cost of the models involved. The current study proposes a method for performing global sensitivity parameter rankings during probabilistic LBB assessments. The study is the continuation of the CANDU nuclear power plant (NPP) pressure tube (PT) case study in El Bouzidi et al., (2024) where a probabilistic approach was implemented in RAVEN (Rabiti and Alfonsi, 2019) to estimate whether the probability of unstable crack growth in PTs is within acceptable limits. This follow-up work proposes surrogate modeling using a high-dimensional model representation to derive Sobol indices and establish a parameter influence ranking. The methodology is demonstrated in a Monte Carlo simulation campaign of a pressure tube inlet rolled joint. The implemented approach successfully identified and quantified critical parameters of the model while efficiently ranking and quantifying the interactions between input variables.
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页数:13
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