An Extended Rosenthal’s Model for Laser Powder-Bed Fusion Additive Manufacturing: Energy Auditing of Thermal Boundary Conditions

被引：4
作者：
Imani Shahabad S. [1 ]
Karimi G. [2 ]
Toyserkani E. [1 ]
机构：
[1] Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, N2L 3G1, ON
[2] Department of Chemical Engineering, Shiraz University, Shiraz
来源：
Lasers in Manufacturing and Materials Processing | 2021年 / 8卷 / 03期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Additive manufacturing; Analytical modeling; Laser powder-bed fusion; Rosenthal equation; Stainless steel; Temperature distribution;
D O I：
10.1007/s40516-021-00148-0
中图分类号：
学科分类号：
摘要：
Laser Powder-Bed Fusions (LPBF), a class of additive manufacturing (AM), is a promising technique for producing components with complex geometry design. However, parts fabricated by LPBF suffer from residual stresses arising due to substantial temperature gradients inherent to the process. Numerical models are unable to provide a comprehensive thermal history of the built materials efficiently due to the mismatch between the characteristic length scales and infinitesimal time steps needed for complete simulations. In the present work, an extended Rosenthal’s model is presented by considering the effects of various heat dissipation/consumption mechanisms. The modeling results of energy auditing of thermal boundary conditions for stainless steel (SS17-4PH) laser melting indicated that the total energy losses by convection, radiation, and melting are less than 20% among which, radiation is the most dominant part. A comparison of the results obtained by the extended Rosenthal’s equation with finite element numerical predictions and experimental data shows a good agreement. Also, a parametric study has been conducted to identify the influence of laser scanning velocity, beam radius, and power on the overall temperature distributions and melt geometry. The present study can pave the way for the prospective use of this methodology to conduct further investigation such as microstructure analysis and thermo-mechanical modeling which are needed to predict residual stresses and distortions. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
引用
收藏
页码：288 / 311
页数：23
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