contributor author | Katinas, Christopher | |
contributor author | Liu, Shunyu | |
contributor author | Shin, Yung C. | |
date accessioned | 2019-03-17T10:19:58Z | |
date available | 2019-03-17T10:19:58Z | |
date copyright | 10/8/2018 12:00:00 AM | |
date issued | 2019 | |
identifier issn | 1087-1357 | |
identifier other | manu_141_01_011001.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4256081 | |
description abstract | Understanding the capture efficiency of powder during direct laser deposition (DLD) is critical when determining the overall manufacturing costs of additive manufacturing (AM) for comparison to traditional manufacturing methods. By developing a tool to predict the capture efficiency of a particular deposition process, parameter optimization can be achieved without the need to perform a costly and extensive experimental study. The focus of this work is to model the deposition process and acquire the final track geometry and temperature field of a single track deposition of Ti–6Al–4V powder on a Ti–6Al–4V substrate for a four-nozzle powder delivery system during direct laser deposition with a LENS™ system without the need for capture efficiency assumptions by using physical powder flow and laser irradiation profiles to predict capture efficiency. The model was able to predict the track height and width within 2 μm and 31 μm, respectively, or 3.3% error from experimentation. A maximum of 36 μm profile error was observed in the molten pool, and corresponds to errors of 11% and 4% in molten pool depth and width, respectively. Based on experimentation, the capture efficiency of a single track deposition of Ti–6Al–4V was found to be 12.0%, while that from simulation was calculated to be 11.7%, a 2.5% deviation. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Self-Sufficient Modeling of Single Track Deposition of Ti–6Al–4V With the Prediction of Capture Efficiency | |
type | Journal Paper | |
journal volume | 141 | |
journal issue | 1 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4041423 | |
journal fristpage | 11001 | |
journal lastpage | 011001-10 | |
tree | Journal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 001 | |
contenttype | Fulltext | |