Yang Zhihao, Zhang Shiting, Ji Xia, Liang Steven Y
School of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Materials (Basel). 2024 May 27;17(11):2565. doi: 10.3390/ma17112565.
To quantitatively evaluate the effect of the process parameters and the material properties on the temperature in laser powder bed fusion (LPBF), this paper proposed a sensitivity analysis of the temperature based on the validated prediction model. First, three different heat source modes-point heat source, Gaussian surface heat source, and Gaussian body heat source-were introduced. Then, a case study of Ti6Al4V is conducted to determine the suitable range of heat source density for the three different heat source models. Based on this, the effects of laser processing parameters and material thermophysical parameters on the temperature field and molten pool size are quantitatively discussed based on the Gaussian surface heat source. The results indicate that the Gaussian surface heat source and the Gaussian body heat source offer higher prediction accuracy for molten pool width compared to the point heat source under similar processing parameters. When the laser energy density is between 40 and 70 J/mm, the prediction accuracy of the Gaussian surface heat source and the body heat source is similar, and the average prediction errors are 4.427% and 2.613%, respectively. When the laser energy density is between 70 and 90 J/mm, the prediction accuracy of the Gaussian body heat source is superior to that of the Gaussian surface heat source. Among the influencing factors, laser power exerts the greatest influence on the temperature field and molten pool size, followed by scanning speed. In particular, laser power and scan speed contribute 38.9% and 23.5% to the width of the molten pool, 39.1% and 19.6% to the depth of the molten pool, and 38.9% and 21.5% to the maximum temperature, respectively.
为了定量评估工艺参数和材料特性对激光粉末床熔融（LPBF）温度的影响，本文基于经过验证的预测模型提出了一种温度敏感性分析方法。首先，引入了三种不同的热源模式——点热源、高斯面热源和高斯体热源。然后，以Ti6Al4V为例，确定了三种不同热源模型的合适热源密度范围。在此基础上，基于高斯面热源定量讨论了激光加工参数和材料热物理参数对温度场和熔池尺寸的影响。结果表明，在相似加工参数下，与点热源相比，高斯面热源和高斯体热源对熔池宽度的预测精度更高。当激光能量密度在40至70 J/mm之间时，高斯面热源和高斯体热源的预测精度相似，平均预测误差分别为4.427%和2.613%。当激光能量密度在70至90 J/mm之间时，高斯体热源的预测精度优于高斯面热源。在影响因素中，激光功率对温度场和熔池尺寸的影响最大，其次是扫描速度。特别是，激光功率和扫描速度对熔池宽度的贡献分别为38.9%和23.5%，对熔池深度的贡献分别为39.1%和19.6%，对最高温度的贡献分别为38.9%和21.5%。
