A Numerical Study on the Keyhole Formation During Laser Powder Bed Fusion Process

2019 ◽  
Vol 141 (10) ◽  
Author(s):  
Subin Shrestha ◽  
Y. Kevin Chou
Keyword(s):  
Energy Density ◽  
Numerical Study ◽  
High Energy ◽  
High Energy Density ◽  
Computational Domain ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Keyhole Behavior

The dynamic phenomenon of a melt pool during the laser powder bed fusion (LPBF) process is complex and sensitive to process parameters. As the energy density input exceeds a certain threshold, a huge vapor depression may form, known as the keyhole. This study focuses on understanding the keyhole behavior and related pore formation during the LPBF process through numerical analysis. For this purpose, a thermo-fluid model with discrete powder particles is developed. The powder distribution, obtained from a discrete element method (DEM), is incorporated into the computational domain to develop a 3D process physics model using flow-3d. The melt pool formation during the conduction mode and the keyhole mode of melting has been discerned and explained. The high energy density leads to the formation of a vapor column and consequently pores under the laser scan track. Further, the keyhole shape resulted from different laser powers and scan speeds is investigated. The numerical results indicated that the keyhole size increases with the increase in the laser power even with the same energy density. The keyhole becomes stable at a higher power, which may reduce the occurrence of pores during laser scanning.

A Numerical Study on the Keyhole Formation During Laser Powder Bed Fusion Process

2019 ◽  
Author(s):  
Subin Shrestha ◽  
Y. Kevin Chou
Keyword(s):  
Energy Density ◽  
Numerical Study ◽  
High Energy ◽  
High Energy Density ◽  
Computational Domain ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Keyhole Behavior

Abstract The dynamic phenomenon of a melt pool during the laser powder bed fusion (LPBF) process is complex and sensitive to process parameters. As the energy density input exceeds a certain threshold, a huge vapor depression may form, known as the keyhole. This study focuses on understanding the keyhole behavior and related pore formation during the LPBF process through numerical analysis. For this purpose, a thermo-fluid model with discrete powder particles is developed. The powder distribution, obtained from a discrete element method (DEM), is incorporated into the computational domain to develop a 3D process physics model using FLOW-3D. The melt pool formation during the conduction mode and the keyhole mode of melting has been discerned and explained. The high energy density leads to the formation of a vapor column and consequently pores under the laser scan track. Further, the keyhole shape resulted from different laser powers and scan speeds is investigated. The numerical results indicated that the keyhole size increases with the increase in the laser power even with the same energy density. The keyhole becomes stable at a higher power, which may reduce the occurrence of pores during laser scanning.

scholarly journals Laser Powder Bed Fusion of Ti-6Al-2Sn-4Zr-6Mo Alloy and Properties Prediction Using Deep Learning Approaches

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2056
Author(s):  
Hany Hassanin ◽  
Yahya Zweiri ◽  
Laurane Finet ◽  
Khamis Essa ◽  
Chunlei Qiu ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Energy Density ◽  
High Energy ◽  
High Energy Density ◽  
Small Data ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Deep Learning Neural Network

Ti-6Al-2Sn-4Zr-6Mo is one of the most important titanium alloys characterised by its high strength, fatigue, and toughness properties, making it a popular material for aerospace and biomedical applications. However, no studies have been reported on processing this alloy using laser powder bed fusion. In this paper, a deep learning neural network (DLNN) was introduced to rationalise and predict the densification and hardness due to Laser Powder Bed Fusion of Ti-6Al-2Sn-4Zr-6Mo alloy. The process optimisation results showed that near-full densification is achieved in Ti-6Al-2Sn-4Zr-6Mo alloy samples fabricated using an energy density of 77–113 J/mm3. Furthermore, the hardness of the builds was found to increase with increasing the laser energy density. Porosity and the hardness measurements were found to be sensitive to the island size, especially at high energy density. Hot isostatic pressing (HIP) was able to eliminate the porosity, increase the hardness, and achieve the desirable α and β phases. The developed model was validated and used to produce process maps. The trained deep learning neural network model showed the highest accuracy with a mean percentage error of 3% and 0.2% for the porosity and hardness. The results showed that deep learning neural networks could be an efficient tool for predicting materials properties using small data.

scholarly journals Keyhole Formation by Laser Drilling in Laser Powder Bed Fusion of Ti6Al4V Biomedical Alloy: Mesoscopic Computational Fluid Dynamics Simulation versus Mathematical Modelling Using Empirical Validation

Nanomaterials ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 3284
Author(s):  
Asif Ur Rehman ◽  
Muhammad Arif Mahmood ◽  
Fatih Pitir ◽  
Metin Uymaz Salamci ◽  
Andrei C. Popescu ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Density ◽  
Operating Conditions ◽  
Dynamics Simulation ◽  
Powder Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool

In the laser powder bed fusion (LPBF) process, the operating conditions are essential in determining laser-induced keyhole regimes based on the thermal distribution. These regimes, classified into shallow and deep keyholes, control the probability and defects formation intensity in the LPBF process. To study and control the keyhole in the LPBF process, mathematical and computational fluid dynamics (CFD) models are presented. For CFD, the volume of fluid method with the discrete element modeling technique was used, while a mathematical model was developed by including the laser beam absorption by the powder bed voids and surface. The dynamic melt pool behavior is explored in detail. Quantitative comparisons are made among experimental, CFD simulation and analytical computing results leading to a good correspondence. In LPBF, the temperature around the laser irradiation zone rises rapidly compared to the surroundings in the powder layer due to the high thermal resistance and the air between the powder particles, resulting in a slow travel of laser transverse heat waves. In LPBF, the keyhole can be classified into shallow and deep keyhole mode, controlled by the energy density. Increasing the energy density, the shallow keyhole mode transforms into the deep keyhole mode. The energy density in a deep keyhole is higher due to the multiple reflections and concentrations of secondary reflected beams within the keyhole, causing the material to vaporize quickly. Due to an elevated temperature distribution in deep keyhole mode, the probability of pores forming is much higher than in a shallow keyhole as the liquid material is close to the vaporization temperature. When the temperature increases rapidly, the material density drops quickly, thus, raising the fluid volume due to the specific heat and fusion latent heat. In return, this lowers the surface tension and affects the melt pool uniformity.

scholarly journals Numerical study of the impact of vaporisation on melt pool dynamics in Laser Powder Bed Fusion - Application to IN718 and Ti–6Al–4V

2020 ◽  
Vol 35 ◽  
pp. 101249
Author(s):  
Alexis Queva ◽  
Gildas Guillemot ◽  
Clara Moriconi ◽  
Charlotte Metton ◽  
Michel Bellet
Keyword(s):  
Numerical Study ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
The Impact

scholarly journals Processability and Optimization of Laser Parameters for Densification of Hypereutectic Al–Fe Binary Alloy Manufactured by Laser Powder Bed Fusion

Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 320
Author(s):  
Wenyuan Wang ◽  
Naoki Takata ◽  
Asuka Suzuki ◽  
Makoto Kobashi ◽  
Masaki Kato
Keyword(s):  
Energy Density ◽  
Binary Alloy ◽  
Process Window ◽  
Process Conditions ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Deposited Energy ◽  
Scan Speed

Centimeter-sized samples of hypereutectic Al–15 mass% Fe alloy were manufactured by a laser powder bed fusion (L-PBF) process while systematically varying laser power (P) and scan speed (v). The effects on relative density and melt pool depth of L-PBF-manufactured samples were investigated. In comparison with other Al alloys, a small laser process window of P = 77–128 W and v = 0.4–0.8 ms−1 was found for manufacturing macroscopically crack-free samples. A higher v and P led to the creation of macroscopic cracks propagating parallel to the powder-bed plane. These cracks preferentially propagated along the melt pool boundaries decorated with brittle θ-Al13Fe4 phase, resulting in low L-PBF processability of Al–15%Fe alloy. The deposited energy density model (using P·v−1/2) would be useful for identifying the optimum L-PBF process conditions towards densification of Al–15%Fe alloy samples, in comparison with the volumetric energy density (using P·v−1), however, the validity of the model was reduced for this alloy in comparison with other alloys with high thermal conductivities. This is likely due to inhomogeneous microstructures having numerous coarsened θ–Al13Fe4 phases localized at melt pool boundaries. These results provide insights into achieving sufficient L-PBF processability for manufacturing dense Al–Fe binary alloy samples.

scholarly journals Melt Pool Features Analysis Using a High Speed Coaxial Monitoring System for Laser Powder Bed Fusion of Ti-6Al-4V Grade 23

2021 ◽  
Author(s):  
Aditi Thanki ◽  
Louca Goossens ◽  
Agusmian Partogi Ompusunggu ◽  
Mohamad Bayat ◽  
Abdellatif Bey-Temsamani ◽  
...  
Keyword(s):  
Energy Density ◽  
Laser Power ◽  
High Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Porosity Formation ◽  
Powder Bed ◽  
Binary Images ◽  
Melt Pool ◽  
Scan Speed

Abstract In laser powder bed fusion (LPBF), defects such as pores or cracks can seriously affect the final part quality and lifetime. Keyhole porosity, being one type of porosity defects in LPBF, results from excessive energy density which may be due to changes in process parameters (laser power and scan speed) and/or result from the part’s geometry and/or hatching strategies. To study the possible occurrence of keyhole pores, experimental work as well as simulations were carried out for optimum and high volumetric energy density conditions in Ti-6Al-4V grade 23. By decreasing the scanning speed from 1000 mm/s to 500 mm/s for a fixed laser power of 170 W, keyhole porosities are formed and later observed by X-ray computed tomography. Melt pool images are recorded in real-time during the LPBF process by using a high speed coaxial Near-Infrared (NIR) camera monitoring system. The recorded images are then pre-processed using a set of image processing steps to generate binary images. From the binary images, geometrical features of the melt pool and features that characterize the spatter particles formation and ejection from the melt pool are calculated. The experimental data clearly show spatter patterns in case of keyhole porosity formation at low scan speed. A correlation between the number of pores and the amount of spatter is observed. Besides the experimental work, a previously developed, high fidelity finite volume numerical model was used to simulate the melt pool dynamics with similar process parameters as in the experiment. Simulation results illustrate and confirm the keyhole porosity formation by decreasing laser scan speed.

scholarly journals On the Relevance of Volumetric Energy Density in the Investigation of Inconel 718 Laser Powder Bed Fusion

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 538 ◽  
Author(s):  
Fabrizia Caiazzo ◽  
Vittorio Alfieri ◽  
Giuseppe Casalino
Keyword(s):  
Surface Roughness ◽  
Energy Density ◽  
Process Parameters ◽  
Vickers Hardness ◽  
Powder Bed Fusion ◽  
Processing Conditions ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Fractional Density ◽  
Experimental Variation

Laser powder bed fusion (LPBF) can fabricate products with tailored mechanical and surface properties. In fact, surface texture, roughness, pore size, the resulting fractional density, and microhardness highly depend on the processing conditions, which are very difficult to deal with. Therefore, this paper aims at investigating the relevance of the volumetric energy density (VED) that is a concise index of some governing factors with a potential operational use. This paper proves the fact that the observed experimental variation in the surface roughness, number and size of pores, the fractional density, and Vickers hardness can be explained in terms of VED that can help the investigator in dealing with several process parameters at once.

scholarly journals Optimization of Laser Powder Bed Fusion Processing Using a Combination of Melt Pool Modeling and Design of Experiment Approaches: Density Control

2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Morgan Letenneur ◽  
Alena Kreitcberg ◽  
Vladimir Brailovski
Keyword(s):  
Scanning Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Density Prediction ◽  
Melt Pool ◽  
Density Control ◽  
Pool Model ◽  
Conventional Material ◽  
Prediction Approach

A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

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