Tension anisotropy of rolled AA7075-T6 auminium alloy: Experiments, BP-Neural network modeling and orientation dependent failure mechanisms

Pub Date : 2024-07-01 DOI:10.1166/mex.2024.2716
L. Lv, Wei William Lee, Hui Lin, Tao Jin
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Abstract

This paper presents the investigations on anisotropic tension mechanical responses of AA7075-T6 based on experiments, classical strength theory, BP-neural network modeling and fracture morphology characterization. Results show that the tension strength anisotropy weakens with deformation degree. Compared to the traditional method, the machine learning model exhibits more flexible in solving the anisotropic plastic responses of AA7075-T6 auminium alloy sheet and provides more accurate predictions. Through analyzing the fracture surface of tension specimen at various orientations, the failure mechanism is sensitive to orientation. Specifically, the irregular distribution of dimples zones and cleavage steps can be observed at lower material orientation. As the orientation increases, the alternative occurrence of ductile and brittle features dominates the failure mechanism. The medium-size dimple caused by coalescence of small-size dimples represents a transition between ductile features zone and brittle characteristics region.
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轧制 AA7075-T6 铝合金的张力各向异性:实验、BP-神经网络建模和取向相关失效机制
本文基于实验、经典强度理论、BP 神经网络建模和断口形态表征,对 AA7075-T6 的各向异性拉伸力学响应进行了研究。结果表明,拉伸强度各向异性随变形程度而减弱。与传统方法相比,机器学习模型在求解 AA7075-T6 铝合金板材各向异性塑性响应时表现出更大的灵活性,并能提供更准确的预测。通过分析不同取向的拉伸试样断裂面,可以发现其破坏机制对取向非常敏感。具体来说,在材料取向较低时,可以观察到凹陷区和劈裂台阶的不规则分布。随着取向的增加,韧性和脆性特征的交替出现主导了破坏机制。由小尺寸凹痕凝聚而成的中等尺寸凹痕代表了韧性特征区和脆性特征区之间的过渡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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