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| Mechanical Property Prediction of Welding Joint Based on Artifi cial Neural Network for Titanium Alloy |
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Abstract The mechanical properties of gas tungsten arc welding (GTAW) are simulated predicted by multilayer forward neural network model for titanium alloys. The input parameters of the neural network are alloy compositions, cooling rate and heat treatment conditions, and the output parameters of the neural network are five important mechanical properties of the weld metal of titanium alloys, namely ultimate tensile strength, elongation, reduction of area, yield strength and hardness. The effects of aluminum and vanadium on mechanical properties were investigated in detail.
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ZHAO Bing, YANG Yi, LI Zhiqiang, MU Yanhong, LIU Shengjing, ZHANG Bin, ZHANG Chao, SUN Chaoyang, LIU Yang, WANG Xinzhu, CHU Xingrong, HAN Shu. Research on SPF/DB Process and Properties of Titanium Alloy Hollow Lattice[J]. Aeronautical Manufacturing Technology, 2023, 66(9): 24-35. |
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2009, 
