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contributor authorKatinas, Christopher
contributor authorLiu, Shunyu
contributor authorShin, Yung C.
date accessioned2019-03-17T10:19:58Z
date available2019-03-17T10:19:58Z
date copyright10/8/2018 12:00:00 AM
date issued2019
identifier issn1087-1357
identifier othermanu_141_01_011001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4256081
description abstractUnderstanding 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.
publisherThe American Society of Mechanical Engineers (ASME)
titleSelf-Sufficient Modeling of Single Track Deposition of Ti–6Al–4V With the Prediction of Capture Efficiency
typeJournal Paper
journal volume141
journal issue1
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.4041423
journal fristpage11001
journal lastpage011001-10
treeJournal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 001
contenttypeFulltext


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