scholarly journals Laser Melting Deposition Additive Manufacturing of Ti6Al4V Biomedical Alloy: Mesoscopic In-Situ Flow Field Mapping via Computational Fluid Dynamics and Analytical Modelling with Empirical Testing

Materials ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 7749
Author(s):  
Muhammad Arif Mahmood ◽  
Asif Ur Rehman ◽  
Fatih Pitir ◽  
Metin Uymaz Salamci ◽  
Ion N. Mihailescu
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Laser Beam ◽  
Melt Flow ◽  
Laser Melting ◽  
Melt Pool ◽  
Industrial Sectors ◽  
Layer Deposition ◽  
Computational Fluid Dynamics Cfd ◽  
Laser Melting Deposition

Laser melting deposition (LMD) has recently gained attention from the industrial sectors due to producing near-net-shape parts and repairing worn-out components. However, LMD remained unexplored concerning the melt pool dynamics and fluid flow analysis. In this study, computational fluid dynamics (CFD) and analytical models have been developed. The concepts of the volume of fluid and discrete element modeling were used for computational fluid dynamics (CFD) simulations. Furthermore, a simplified mathematical model was devised for single-layer deposition with a laser beam attenuation ratio inherent to the LMD process. Both models were validated with the experimental results of Ti6Al4V alloy single track depositions on Ti6Al4V substrate. A close correlation has been found between experiments and modelling with a few deviations. In addition, a mechanism for tracking the melt flow and involved forces was devised. It was simulated that the LMD involves conduction-mode melt flow only due to the coaxial addition of powder particles. In front of the laser beam, the melt pool showed a clockwise vortex, while at the back of the laser spot location, it adopted an anti-clockwise vortex. During printing, a few partially melted particles tried to enter into the molten pool, causing splashing within the melt material. The melting regime, mushy area (solid + liquid mixture) and solidified region were determined after layer deposition. This research gives an in-depth insight into the melt flow dynamics in the context of LMD printing.

scholarly journals Mesoscopic Computational Fluid Dynamics Modelling for the Laser-Melting Deposition of AISI 304 Stainless Steel Single Tracks with Experimental Correlation: A Novel Study

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1569
Author(s):  
Asif Ur Rehman ◽  
Muhammad Arif Mahmood ◽  
Fatih Pitir ◽  
Metin Uymaz Salamci ◽  
Andrei C. Popescu ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Laser Beam ◽  
Marangoni Convection ◽  
304 Stainless Steel ◽  
Laser Melting ◽  
Aisi 304 Stainless Steel ◽  
Aisi 304 ◽  
Melt Pool ◽  
Powder Particles ◽  
Laser Melting Deposition

For laser-melting deposition (LMD), a computational fluid dynamics (CFD) model was developed using the volume of fluid and discrete element modeling techniques. A method was developed to track the flow behavior, flow pattern, and driving forces of liquid flow. The developed model was compared with experimental results in the case of AISI 304 stainless steel single-track depositions on AISI 304 stainless steel substrate. A close correlation was found between experiments and modeling, with a deviation of 1–3%. It was found that the LMD involves the simultaneous addition of powder particles that absorb a significant amount of laser energy to transform their phase from solid to liquid, resulting in conduction-mode melt flow. The bubbles within the melt pool float at a specific velocity and escape from the melt pool throughout the deposition process. The pores are generated if the solid front hits the bubble before escaping the melt pool. Based on the simulations, it was discovered that the deposited layer’s counters took the longest time to solidify compared to the overall deposition. The bubbles strived to leave through the contours in an excess quantity, but became stuck during solidification, resulting in a large degree of porosity near the contours. The stream traces showed that the melt flow adopted a clockwise vortex in front of the laser beam and an anti-clockwise vortex behind the laser beam. The difference in the surface tension between the two ends of the melt pool induces “thermocapillary or Benard–Marangoni convection” force, which is insignificant compared to the selective laser melting process. After layer deposition, the melt region, mushy zone, and solidified region were identified. When the laser beam irradiates the substrate and powder particles are added simultaneously, the melt adopts a backwards flow due to the recoil pressure and thermocapillary or Benard–Marangoni convection effect, resulting in a negative mass flow rate. This study provides an in-depth understanding of melt pool dynamics and flow pattern in the case of LMD additive manufacturing technique.

Efficiency prediction for storage chambers using computational fluid dynamics

1996 ◽  
Vol 33 (9) ◽  
pp. 163-170 ◽  
Author(s):  
Virginia R. Stovin ◽  
Adrian J. Saul
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shear Stress ◽  
Particle Tracking ◽  
Critical Value ◽  
Complex Geometries ◽  
Bed Shear Stress ◽  
Breadth Ratio ◽  
Computational Fluid Dynamics Cfd ◽  
Simulated Flow

Research was undertaken in order to identify possible methodologies for the prediction of sedimentation in storage chambers based on computational fluid dynamics (CFD). The Fluent CFD software was used to establish a numerical model of the flow field, on which further analysis was undertaken. Sedimentation was estimated from the simulated flow fields by two different methods. The first approach used the simulation to predict the bed shear stress distribution, with deposition being assumed for areas where the bed shear stress fell below a critical value (τcd). The value of τcd had previously been determined in the laboratory. Efficiency was then calculated as a function of the proportion of the chamber bed for which deposition had been predicted. The second method used the particle tracking facility in Fluent and efficiency was calculated from the proportion of particles that remained within the chamber. The results from the two techniques for efficiency are compared to data collected in a laboratory chamber. Three further simulations were then undertaken in order to investigate the influence of length to breadth ratio on chamber performance. The methodology presented here could be applied to complex geometries and full scale installations.

Improvement of real-scale raceway bioreactors for microalgae production using Computational Fluid Dynamics (CFD)

2021 ◽  
Vol 54 ◽  
pp. 102207
Author(s):  
Cristian Inostroza ◽  
Alessandro Solimeno ◽  
Joan García ◽  
José M. Fernández-Sevilla ◽  
F. Gabriel Acién
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Computational Fluid Dynamics Cfd ◽  
Real Scale
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