scholarly journals A simplified model for numerical simulation of laser metal deposition process with beam oscillation

2018 ◽  
Vol 1109 ◽  
pp. 012006 ◽  
Author(s):  
S Y Ivanov ◽  
A Artinov ◽  
E A Valdaytseva ◽  
S L Stankevich ◽  
G A Turichin
Keyword(s):  
Numerical Simulation ◽  
Deposition Process ◽  
Metal Deposition ◽  
Simplified Model ◽  
Laser Metal Deposition ◽  
Beam Oscillation

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.

Study of TI64 Vibration Laser Metal Deposition Process

2011 ◽  
Vol 189-193 ◽  
pp. 512-517 ◽  
Author(s):  
Xue Yong Chen ◽  
Todd Sparks ◽  
Jian Zhong Ruan ◽  
Frank Liou
Keyword(s):  
Design Of Experiments ◽  
Grain Refinement ◽  
Crystalline Structure ◽  
Vibration Frequency ◽  
Deposition Process ◽  
Metal Deposition ◽  
Laser Deposition ◽  
Laser Metal Deposition ◽  
Direct Deposition ◽  
Laser Direct Deposition

This paper presents the usage of vibration in laser direct deposition of Ti64. The vibration is used to refine the crystalline structure of the deposition. The vibration device vibrates in the laser deposition system along the Z axis. A design of experiments approach is applied in studying the effect of vibration on the deposited material. Vibration during deposition led to grain refinement and an increase in microhardness over that of samples from no-vibration. Also, vibration frequency is a significant factor. From the experiment results, it is found that a vibration frequency greater than 20Hz is desirable.

Vision-based defect detection in laser metal deposition process

2014 ◽  
Vol 20 (1) ◽  
pp. 77-85 ◽  
Author(s):  
Shyam Barua ◽  
Frank Liou ◽  
Joseph Newkirk ◽  
Todd Sparks
Keyword(s):  
Defect Detection ◽  
Detection System ◽  
Vision System ◽  
Low Cost ◽  
Deposition Process ◽  
Metal Deposition ◽  
Cooling Curve ◽  
Laser Metal Deposition ◽  
Content Type ◽  
Melt Pool

Purpose – Laser metal deposition (LMD) is a type of additive manufacturing process in which the laser is used to create a melt pool on a substrate to which metal powder is added. The powder is melted within the melt pool and solidified to form a deposited track. These deposited tracks may contain porosities or cracks which affect the functionality of the part. When these defects go undetected, they may cause failure of the part or below par performance in their applications. An on demand vision system is required to detect defects in the track as and when they are formed. This is especially crucial in LMD applications as the part being repaired is typically expensive. Using a defect detection system, it is possible to complete the LMD process in one run, thus minimizing cost. The purpose of this paper is to summarize the research on a low-cost vision system to study the deposition process and detect any thermal abnormalities which might signify the presence of a defect. Design/methodology/approach – During the LMD process, the track of deposited material behind the laser is incandescent due to heating by the laser; also, there is radiant heat distribution and flow on the surfaces of the track. An SLR camera is used to obtain images of the deposited track behind the melt pool. Using calibrated RGB values and radiant surface temperature, it is possible to approximate the temperature of each pixel in the image. The deposited track loses heat gradually through conduction, convection and radiation. A defect-free deposit should show a gradual decrease in temperature which enables the authors to obtain a reference cooling curve using standard deposition parameters. A defect, such as a crack or porosity, leads to an increase in temperature around the defective region due to interruption of heat flow. This leads to deviation from the reference cooling curve which alerts the authors to the presence of a defect. Findings – The temperature gradient was obtained across the deposited track during LMD. Linear least squares curve fitting was performed and residual values were calculated between experimental temperature values and line of best fit. Porosity defects and cracks were simulated on the substrate during LMD and irregularities in the temperature gradients were used to develop a defect detection model. Originality/value – Previous approaches to defect detection in LMD typically concentrate on the melt pool temperature and dimensions. Due to the dynamic and violent nature of the melt pool, consistent and reliable defect detection is difficult. An alternative method of defect detection is discussed which does not involve the melt pool and therefore presents a novel method of detecting a defect in LMD.

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