Real-time monitoring of stress corrosion cracking in 304 L stainless steel pipe using acoustic emission

声发射 应力腐蚀开裂 材料科学 波形 信号(编程语言) 缩颈 开裂 振幅 极限抗拉强度 压力(语言学) 腐蚀 复合材料 断裂力学 电压 电气工程 工程类 光学 物理 哲学 语言学 程序设计语言 计算机科学
作者
Jaewoong Park,Kim Js,Dae Young Lee,Seung Hwan Lee
出处
期刊:Journal of Nuclear Materials [Elsevier]
卷期号:571: 154009-154009 被引量:12
标识
DOI:10.1016/j.jnucmat.2022.154009
摘要

A stress corrosion cracking (SCC) monitoring indicator (MI) based on the acoustic emission (AE) technique is proposed for the real-time detection and monitoring of SCC initiation in 304 L stainless steel (SS) pipes used for the primary circuits of nuclear power plants (NPPs). A device is used to accelerate the initiation of SCC to shorten the experiment timeframe. A non-crack AE signal criterion was established, which was conducted by injecting an etchant and distilled water into 304 L SS pipe specimens as experimental and control groups, respectively. Furthermore, to characterize the AE signal responsible for cracking, the characteristics of the AE signal measured in the section between necking and fracture (where cracks occur and propagate) among the stress curves obtained from the 304 L SS tensile test using AE sensors were investigated. Subsequently, the maximum amplitude, energy, frequency characteristics (range and magnitude), and waveform of the remaining AE signals were investigated after removing some AE signals by applying the non-crack AE signal criterion in the experiment where the SCC penetrated the pipe. These were compared with the maximum amplitude, energy, frequency characteristics, and waveform which were investigated in the tensile test to derive common characteristics for the two sets of crack signals to establish an SCC MI. To evaluate the performance of the developed SCC MI, the SCC monitoring experiment was halted when AE signals corresponding to the SCC MI criteria were measured, to fabricate a pipe wherein non-penetrating SCC was formed. In this manner, by applying the SCC MI to detect SCC in real time, we verified that the SCC MI had excellent SCC detection performance. Furthermore, we performed scanning electron microscopy (SEM) image analyses and SEM-energy dispersive X-ray spectrometry analyses to investigate the causes of SCC propagation.
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