Metals and Materials International ( IF 3.3 ) Pub Date : 2021-07-29 , DOI: 10.1007/s12540-021-00995-8 Erfan Maleki 1 , Mario Guagliano 1 , Sara Bagherifard 1 , Okan Unal 2
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In this study, the effect of kinetic energy of the shot peening process on microstructure, mechanical properties, residual stress, fatigue behavior and residual stress relaxation under fatigue loading of AISI 316L stainless steel were investigated to figure out the mechanisms of fatigue crack initiation and failure. Varieties of experiments were applied to obtain the results including microstructural observations, measurements of hardness, roughness, induced residual stress and residual stress relaxation as well as axial fatigue test. Then deep learning approach through neural networks was used for modelling of mechanical properties and fatigue behavior of shot peened material. Comprehensive parametric analyses were performed to survey the effects of different key parameters. Afterward, according to the results of neural network analysis, further experiments were performed to optimize and experimentally validate the desirable parameters. Based on the obtained results the favorable range of shot peening coverage regarding improved mechanical properties and fatigue behavior was identified as no more than 1750% considering Almen intensity of 21 A (0.001 inch).
Graphic abstract
中文翻译：
通过深度学习方法分析经过喷丸处理的梯度纳米结构 316L 钢的疲劳行为和残余应力松弛
本研究通过研究喷丸过程动能对AISI 316L不锈钢疲劳载荷下的显微组织、力学性能、残余应力、疲劳行为和残余应力松弛的影响，以找出疲劳裂纹萌生和失效的机制。 . 应用各种实验来获得结果，包括微观结构观察、硬度测量、粗糙度、诱导残余应力和残余应力松弛以及轴向疲劳试验。然后通过神经网络的深度学习方法用于对喷丸材料的机械性能和疲劳行为进行建模。进行了综合参数分析以调查不同关键参数的影响。之后，根据神经网络分析的结果，进行了进一步的实验以优化和实验验证所需的参数。根据获得的结果，考虑到 21 A（0.001 英寸）的阿尔门强度，喷丸强化覆盖的有利范围被确定为不超过 1750%。
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