Correlating Laser Additive Manufacturing Process with Heat Source Coefficients by Integrated Experimental and Numerical Models

Numerical modeling of additive manufacturing processes is often conducted to predict both thermal and mechanical effects such as distortions, residual stresses, and phase distributions. The prediction accuracy is highly dependent on an accurate representation of thermal field, especially heat sources. In this study, response surface methodology (RSM) is serially utilized and mutually mapped to understand the relationships between process parameters and heat source coefficients. First, the effects of process factors and heat source model coefficients on experimental and numerical bead geometry are, respectively, identified through analysis of variance on central composite designs. With influences mathematically quantified, heat source coefficients in accordance with experimental conditions are inversely solved using nonlinear least square method, followed by correlation with process factors. The results show that both the effects of process parameters and heat source coefficients on bead geometry characteristics can be modeled using quadratic polynomials. The connections between heat source coefficients and process variables can also be modeled using quadratic or lower polynomial functions with good accuracy. It is proven that the proposed RSM mapping method is feasible for heat process correlation. The research outcome provides a convenient and reliable method of heat source calibration for laser additive manufacturing.