Numerical investigation of thermal behavior and melt pool morphology in multi-track multi-layer selective laser melting of the 316L steel

Waqar, Saad; Sun, Qidong; Liu, Jiangwei; Guo, Kai; Sun, Jie

doi:10.1007/s00170-020-06360-0

Cited by 56 publications

(14 citation statements)

References 41 publications

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“…The multi-track, multi-layer, and multi-material SLM process was modeled by the discrete element method [ 49 ]. Numerical tools were developed for obtaining reliable processing windows [ 50 ] and studying the thermal behavior, and melt pool morphology in the multi-track multi-layer SLM of SS316L [ 51 ].…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting

et al. 2021

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In this work, dimensional analysis is used to develop a general mathematical model to predict bulk density of SLMed components taking volumetric energy density, scanning speed, powder’s thermal conductivity, specific heat capacity, and average grain diameter as independent variables. Strong relation between dependent and independent dimensionless products is observed. Inconel 718 samples were additively manufactured and a particular expression, in the form of a power-law polynomial, for its bulk density, in the working domain of the independent dimensionless product, was obtained. It is found that with longer laser exposure time, and lower scanning speed, better densification is attained. Likewise, volumetric energy density has a positive influence on bulk density. The negative effect of laser power in bulk density is attributed to improper process conditions leading to powder particle sublimation and ejection. A maximum error percentage between experimental and predicted bulk density of 3.7119% is achieved, which corroborates the accuracy of our proposed model. A general expression for determining the scanning speed, with respect to laser power, needed to achieve highly dense components, was derived. The model’s applicability was further validated considering SLMed samples produced by AlSi10Mg and Ti6Al4V alloys. This article elucidates how to tune relevant manufacturing parameters to produce highly dense SLM parts using mathematical expressions derived from Buckingham’s π- theorem.

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Section: Introductionmentioning

confidence: 99%

A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting

et al. 2021

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“…The forming characteristics of melt pool morphologies between adjacent scanning tracks and layers and the effect of melt pool morphology on the final forming geometry of SLM object would be covered in future work. Liquid specific heat capacity 𝐶 𝑙 (J/(kgK)) 720 [40] 872 [41] 770 [3] Solid specific heat capacity 𝐶 𝑠 (J/(kgK)) 435 [40] 763 [41] 680 [3] Latent heat of fusion ℎ sl (J/kg) 2.1e 5 3.65e 5 2.7e 5 Thermal conductivity 𝑘(W/(mK)) 24.1 [42] 21 [42] 36 [42] Boiling temperature 𝑇 𝑏 (K) 3111 [40] 3300 [3] 3273 [15] Melting temperature 𝑇 𝑚 (K) 1609 [42] 1928 [30] 1700 [3] Convection coefficient 𝛼 𝑔 (W(m 2 K)) 8 [43] 10 [44] 100 [45] Thermal radiation coefficient 𝜀 0.32 [40] 0.43 [8] 0.35 [45] Density 𝜌(kg/m 3 ) 7451 [39] 4000 [41] 7800 [42] Powder compaction rate 𝜌 𝑝 /𝜌 𝑠 0.6 [11] 0.6 [11] 0.6 [11] Stefan-Boltzmann coefficient 𝜎(W/(m 2 K 4 )) 5.67e -8 5.67e -8 5.67e -8 Appendix B Adopted energy absorptivity under different machines and process conditions for IN718, TC4 and 316L…”

Section: Discussionmentioning

confidence: 99%

A Computational Model of Melt Pool Morphology for Selective Laser Melting Process

Qiao

Huang

et al. 2021

Preprint

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Selective laser melting (SLM) is a promising metal additive manufacturing technology, which holds widespread applications in numerous fields. Unfortunately, it is arduous to predict the real SLM part geometry, which impedes its further development. While the morphology of melt pool, influenced and determined by process parameters, poses a crucial influence on the overall part geometry. Nonetheless, the association between process parameters and melt pool morphology is still unclear. Hence it is indispensable to explore relevant solution to address this issue. For this purpose, this paper proposes a new model to directly establish the mathematical relationship between process parameters and melt pool structure for SLM process. In this model, the status of melt pool is first qualitatively analyzed via the defined synthetic process index, and three types of melting states are differentiated including low melting, intermediate melting and high melting, which could cover different melt pool modes. Then, the computational model involving more physical mechanisms integrating mass conversion, heat exchange and temperature field is constructed. Melt pool critical geometries including the height, width, depth and length could be computed through the model. In order to validate the correctness of the proposed model, published experimental observations and existing models are compared. Calculation results from the proposed model show high consistency with the experimental samples and better accuracy than existing empirical models. Its applicability in melt pool classification and prediction is also verified, laying foundation for geometric simulation of SLM object which is successively shaped melt-pool by melt-pool.

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“…It has been reported [36,37] that the material properties can affect meltpool features. Therefore, to have a comprehensive model with higher accuracy, a material-based model including thermophysical properties is intended [38].…”

Section: Developing a Model To Calculate The Meltpool Depthmentioning

confidence: 99%

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

Khorasani

Ghasemi

Leary³

et al. 2022

Int J Adv Manuf Technol

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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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Numerical investigation of thermal behavior and melt pool morphology in multi-track multi-layer selective laser melting of the 316L steel

Cited by 56 publications

References 41 publications

A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting

A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting

A Computational Model of Melt Pool Morphology for Selective Laser Melting Process

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

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