A comprehensive study on meltpool depth in laser-based powder bed fusion of Inconel 718

被引:0
作者
Mahyar Khorasani
AmirHossein Ghasemi
Martin Leary
Laura Cordova
Elmira Sharabian
Ehsan Farabi
Ian Gibson
Milan Brandt
Bernard Rolfe
机构
[1] Royal Melbourne Institute of Technology,School of Engineering
[2] Deakin University,School of Engineering
[3] Australian Institute of Science & Technology,Department of Industrial and Materials Science
[4] Chalmers University of Technology,Insitute for Frontier Material
[5] Deakin University,Fraunhofer Project Centre for Complex System Engineering, Department of Design, Production, and Management
[6] University of Twente,undefined
来源
The International Journal of Advanced Manufacturing Technology | 2022年 / 120卷
关键词
Additive manufacturing; Meltpool depth; Laser-based powder bed fusion; Laser irradiation; Wavelength;
D O I
暂无
中图分类号
学科分类号
摘要
One problematic task in the laser-based powder bed fusion (LB-PBF) process is the estimation of meltpool depth, which is a function of the process parameters and thermophysical properties of the materials. In this research, the effective factors that drive the meltpool depth such as optical penetration depth, angle of incidence, the ratio of laser power to scan speed, surface properties and plasma formation are discussed. The model is useful to estimate the meltpool depth for various manufacturing conditions. A proposed methodology is based on the simulation of a set of process parameters to obtain the variation of meltpool depth and temperature, followed by validation with reference to experimental test data. Numerical simulation of the LB-PBF process was performed using the computational scientific tool “Flow3D Version 11.2” to obtain the meltpool features. The simulation data was then developed into a predictive analytical model for meltpool depth and temperature based on the thermophysical powder properties and associated parameters. The novelty and contribution of this research are characterising the fundamental governing factors on meltpool depth and developing an analytical model based on process parameters and powder properties. The predictor model helps to accurately estimate the meltpool depth which is important and has to be sufficient to effectively fuse the powder to the build plate or the previously solidified layers ensuring proper bonding quality. Results showed that the developed analytical model has a high accuracy to predict the meltpool depth. The model is useful to rapidly estimate the optimal process window before setting up the manufacturing tasks and can therefore save on lead-time and cost. This methodology is generally applied to Inconel 718 processing and is generalisable for any powder of interest. The discussions identified how the effective physical factors govern the induced heat versus meltpool depth which can affect the bonding and the quality of LB-PBF components.
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页码:2345 / 2362
页数:17
相关论文
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