Abstract

The evaluation of the reliability and integrity of a structure consists of proving its ability to fulfill these mechanical functions for all loading modes, normal or accidental, and throughout its lifetime. In the context of nuclear safety, the most important structures consider the presence of degradation encompassing several aspects, such as cracks. In this context, this study proposes an integrated approach to assess the probability of failure due to stress corrosion cracking (SCC) of piping in nuclear power plants. It utilizes Monte Carlo simulation (SMC), probabilistic fracture mechanics (MRP) using the M-PRAISE calculation program, sensitivity analysis, and artificial neural networks (ANN) to effectively estimate the reliability of damaged pipes. Focusing on austenitic stainless steels, this analysis also includes simulation of SCC and the use of damage parameters dependent on residual stresses, environmental conditions, and the degree of sensitization consolidating the influences of different factors to evaluate crack growth rates and initiation time. Additionally, it examines the impact of replacing the old material AISI304 with the new material AISI316 and predicts the effectiveness of in-service inspection (ISI) programs on the reliability of stainless-steel piping systems under SCC conditions.
The analysis highlights the importance of a reinforced inspection program, combining crack detection and appropriate inspection schedules, to ensure the safety of piping against rapid crack growth. In conclusion, this work offers essential perspectives for enhancing the reliability and durability of piping, thereby contributing to strengthening the safety and long-term performance of these critical facilities.
Keywords:Structural reliability, ANN, MCS, Probabilistic Fracture Mechanics, ISI, Fatigue, IG-SCC, Damage, AISI 304 Steel, AISI 316 Steel.

Information

Item Type:	Thesis
Divisions:	» Faculty of Science and Technology
ePrint ID:	5242
Date Deposited:	2024-12-16
Further Information:	Google Scholar
URI:	https://old.univ-soukahras.dz/en/publication/article/5242

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