材料科学
喷丸
损伤容限
热等静压
残余应力
复合材料
巴黎法
断裂力学
疲劳极限
断裂韧性
直接金属激光烧结
极限抗拉强度
韧性
微观结构
冶金
裂缝闭合
复合数
作者
Thorsten Hermann Becker,Punit Kumar,Upadrasta Ramamurty
出处
期刊:Acta Materialia
[Elsevier BV]
日期:2021-08-15
卷期号:219: 117240-117240
被引量:223
标识
DOI:10.1016/j.actamat.2021.117240
摘要
Additive manufacturing (AM) of metallic components offers many advantages over conventional manufacturing methods, most notably design freedom at little material waste. Consequently, there is significant current interest in the manufacturing aspects of a wide variety of structural alloys. Concomitantly, establishing the processing – microstructure – mechanical performance relations, in conjunction with the attributes such as flaws, residual stresses, and mesostructures inherent to the AM processes, is critical for the widespread adoption of structural metallic components made using AM. Keeping this in view, a comprehensive review of the current understanding of the structure-property correlations in AM alloys is provided here. Unique aspects of the microstructures of the AM alloys, process-related attributes, and their effect on the tensile, fracture, fatigue crack growth, and unnotched fatigue properties are highlighted, with emphasis on the interplay between the microstructures and process attributes in determining the structural integrity of AM alloys in terms of properties such as near-threshold fatigue crack growth rate, fracture toughness, and fatigue strength. These aspects are contrasted with respective structure-property correlations in wrought or cast alloys. Strategies employed for improving the damage tolerance of the alloys through either improvisation of the processing conditions during AM or via post-processing treatments such as annealing, hot-isostatic pressing, and shot peening, are summarized. The existing gaps in understanding fatigue and fracture in AM alloys, which are critical for widespread deployment and reliable design of engineering components, are identified; such gaps are expected to provide future avenues for research in this area.
科研通智能强力驱动
Strongly Powered by AbleSci AI