Fatigue Monitoring of 321 Steel Coated by Laser Additively Manufactured CoCrFeMnNi High-Entropy Alloy Using Acoustic Emission Technique

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Wei Li, Shengnan Hu, Shunpeng Zhu, Cong Li, Guowei Bo, Chipeng Zhang, Dapeng Jiang, Hui Chen, Jianjun He, Wenjun Duan, Jian Chen
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Abstract

Fatigue failure is a common mode of deterioration for steel cables (e.g., 321 stainless steel) in cable-stayed bridges. In this case, given that the FeCoNiCrMn high-entropy alloy (HEA) coatings have been found to simultaneously improve the fatigue and corrosion resistance of 321 steel, the fatigue crack growth behavior of 321 steel coated with selective laser melting CoCrFeMnNi HEA was further studied in this work. The results indicate that the CoCrFeMnNi alloy coating is able to increase the fatigue crack growth resistance of 321 steel by 21.43% compared to the uncoated 321 steel, and this is because the initiation of crack is mitigated by the angular disparities between adjacent grains and an increased dislocation density in the coating. Furthermore, the acoustic emission (AE) technique was used to track fatigue damage and predict fatigue crack growth life. It was found that crack length could be effectively monitored and predicted using the count and energy parameter, suggesting material and stress ratio independence in the AE technique.

Abstract Image

激光增材制备CoCrFeMnNi高熵合金涂层321钢的声发射疲劳监测
疲劳破坏是斜拉桥钢缆(如 321 不锈钢)常见的劣化模式。在这种情况下,鉴于铁钴镍铬锰高熵合金(HEA)涂层可同时提高 321 钢的抗疲劳和耐腐蚀性能,本研究进一步研究了涂有选择性激光熔化钴铬铁镍高熵合金涂层的 321 钢的疲劳裂纹生长行为。结果表明,与未涂层的 321 钢相比,CoCrFeMnNi 合金涂层能将 321 钢的抗疲劳裂纹生长性能提高 21.43%,这是因为相邻晶粒之间的角度差异和涂层中位错密度的增加减轻了裂纹的萌生。此外,还利用声发射(AE)技术跟踪疲劳损伤并预测疲劳裂纹生长寿命。研究发现,利用计数和能量参数可以有效监测和预测裂纹长度,这表明声发射技术与材料和应力比无关。
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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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