scholarly journals A coupled multiphase Lagrangian-Eulerian fluid-dynamics framework for numerical simulation of Laser Metal Deposition process

2021 ◽  
Author(s):  
Mauro Murer ◽  
Giovanni Formica ◽  
Franco Milicchio ◽  
Simone Morganti ◽  
Ferdinando Auricchio
Keyword(s):  
Fluid Dynamics ◽  
Numerical Simulation ◽  
3D Printing ◽  
Deposition Process ◽  
Metal Deposition ◽  
Particle Model ◽  
Laser Metal Deposition ◽  
Metal Powders ◽  
Carrier Gas ◽  
Computational Fluid Dynamics Cfd

Abstract We present a Computational Fluid Dynamics (CFD) framework for the numerical simulation of the Laser Metal Deposition (LMD) process in 3D printing. Such a framework, comprehensive of both numerical formulations and solvers, aims at providing an exhaustive scenario of the process, where the carrier gas, modeled as an Eulerian incompressible fluid, transports metal powders, tracked as Langrangian discrete particles, within the 3D printing chamber. On the basis of heat sources coming from the laser beam and the heated substrate, the particle model is developed to interact with the carrier gas also by heat transfer and to evolve in a melted phase according to a growth law of the particle liquid mass fraction. Enhanced numerical solvers, characterized by a modified Netwon-Raphson scheme and a parallel algorithm for tracking particles, are employed to obtain both e ffi ciency and accuracy of the numerical strategy. In the perspective of investigating optimal design of the whole LMD process, we propose a sensitivity analysis specifically addressed to assess the influence of inflow rates, laser beams intensity, and nozzle channel geometry. Such a numerical campaign is performed with an in-house C++ code developed with the deal.II open source Finite Element library.

scholarly journals Application of Computational Fluid Dynamics (CFD) in the Deposition Process and Printability Assessment of 3D Printing Using Rice Paste

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Timilehin Martins Oyinloye ◽  
Won Byong Yoon
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
3D Printing ◽  
Deposition Process ◽  
Operating Conditions ◽  
Nozzle Diameter ◽  
Cfd Analysis ◽  
Flow Properties ◽  
Swell Ratio ◽  
Computational Fluid Dynamics Cfd

Computational fluid dynamics (CFD) was utilized to investigate the deposition process and printability of rice paste. The rheological and preliminary printing studies showed that paste formed from rice to water ratio (100:80) is suitable for 3D printing (3DP). Controlling the ambient temperature at C also contributed to improving the printed sample’s structural stability. The viscoelastic simulation indicated that the nozzle diameter influenced the flow properties of the printed material. As the nozzle diameter decreased (1.2 mm to 0.8 mm), the die swell ratio increased (13.7 to 15.15%). The rise in the swell ratio was a result of the increasing pressure gradient at the nozzle exit (5.48 × 106 Pa to 1.53 × 107 Pa). The additive simulation showed that the nozzle diameter affected both the residual stress and overall deformation of the sample. CFD analysis, therefore, demonstrates a significant advantage in optimizing the operating conditions for printing rice paste.

An Improved Computational Fluid Dynamics (CFD) Model for Erosion Prediction in Oil and Gas Industry Applications

2014 ◽  
Author(s):  
Deval Pandya ◽  
Brian Dennis ◽  
Ronnie Russell
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Surface Velocity ◽  
Particle Model ◽  
Model Parameters ◽  
Cfd Model ◽  
Erosion Model ◽  
Erosion Prediction ◽  
Erosion Models ◽  
Computational Fluid Dynamics Cfd

In recent years, the study of flow-induced erosion phenomena has gained interest as erosion has a direct influence on the life, reliability and safety of equipment. Particularly significant erosion can occur inside the drilling tool components caused by the low particle loading (<10%) in the drilling fluid. Due to the difficulty and cost of conducting experiments, significant efforts have been invested in numerical predictive tools to understand and mitigate erosion within drilling tools. Computational fluid dynamics (CFD) is becoming a powerful tool to predict complex flow-erosion and a cost-effective method to re-design drilling equipment for mitigating erosion. Existing CFD-based erosion models predict erosion regions fairly accurately, but these models have poor reliability when it comes to quantitative predictions. In many cases, the error can be greater than an order of magnitude. The present study focuses on development of an improved CFD-erosion model for predicting the qualitative as well as the quantitative aspects of erosion. A finite-volume based CFD-erosion model was developed using a commercially available CFD code. The CFD model involves fluid flow and turbulence modeling, particle tracking, and application of existing empirical erosion models. All parameters like surface velocity, particle concentration, particle volume fraction, etc., used in empirical erosion equations are obtained through CFD analysis. CFD modeling parameters like numerical schemes, turbulence models, near-wall treatments, grid strategy and discrete particle model parameters were investigated in detail to develop guidelines for erosion prediction. As part of this effort, the effect of computed results showed good qualitative and quantitative agreement for the benchmark case of flow through an elbow at different flow rates and particle sizes. This paper proposes a new/modified erosion model. The combination of an improved CFD methodology and a new erosion model provides a novel computational approach that accurately predicts the location and magnitude of erosion. Reliable predictive methodology can help improve designs of downhole equipment to mitigate erosion risk as well as provide guidance on repair and maintenance intervals. This will eventually lead to improvement in the reliability and safety of downhole tool operation.

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