基于村上法的增材制造铝合金疲劳抗力分析预测

Matthias Oberreiter, Nik Nur Khaleeda Nik Norzainal Abidin,, Michael Stoschka, Yupiter HP Manurung, Mohd Shahriman Adenan, Renga Rao Krishnamoorthy
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摘要

采用电弧增材制造(WAAM)技术对一种新研制的高强度铝合金试样进行了应力状态和疲劳强度分析。基于传统村上方程参数的平方根面积,计算了裂纹尺寸与疲劳强度的关系。村上方程是预测金属材料抗疲劳性能的一种常用分析方法。研究了HS-Al-A和HS-Al-B两种铝合金的金相制备过程,并进行了维氏硬度测定。然后,利用开源软件ImageJ对观察到的孔隙图像进行处理,考虑像素和实际距离,并定义图像阈值来测量孔隙大小。为了描述裂纹前沿的最大应力强度因子Kmax和评定疲劳强度σFS,采用了解析方法。最终试样A的平均孔隙面积≈65µm, Kmax为333.75 MPa∙√m, σFS为137 MPa;试样B的平均孔隙面积≈42µm, Kmax为325.13 MPa∙√m, σFS为153 MPa。总的来说,本研究建立了一种估算大缺陷疲劳强度的方法,得出缺陷会影响材料的抗疲劳性能,缺陷尺寸越大,σFS越低,Kmax越高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytical prediction of fatigue resistance of additively manufactured aluminium alloy based on Murakami method
This research is devoted to analyze the stress state and fatigue strength of two specimens made by a newly developed high-strength aluminium alloy produced by the wire arc additive manufacturing (WAAM) process. The relationship between fatigue strength and flaw size was calculated based on the root squared area – a parameter by conventional Murakami’s equation which is a widely used analytical approach for predicting fatigue resistance in metallic materials. The research involves the metallographic preparation process on two aluminum alloy labeled HS-Al-A and HS-Al-B followed by Vickers hardness measurement. Further, the image of the observed pores was processed and dimensioned using an open-sourced software ImageJ by considering pixels and actual distance as well as by defining image threshold value for measuring pore sizes. The analytical approach is conducted in order to describe the maximum stress intensity factor Kmax at the crack front and to assess the fatigue strength σFS. As final results, specimen A has an average pore area of ≈65 µm with Kmax of 333.75 MPa∙√m and σFS of 137 MPa, while specimen B has an average pore area of ≈42 µm with Kmax of 325.13 MPa∙√m and σFS of 153 MPa. Overall, this research allows the formulation of a method for estimating fatigue strength of large defects leading to a conclusion that flaws can influence the fatigue resistance of the material so that the bigger the flaw size is, the lower σFS and the higher the Kmax.
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