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Prediction of Residual Stress and Distortion in Laser Powder Bed Fusion Additive Manufacturing.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Prediction of Residual Stress and Distortion in Laser Powder Bed Fusion Additive Manufacturing./
作者:	Kosaraju, Bhanuprakash Sairam.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	74 p.
附註:	Source: Masters Abstracts International, Volume: 83-03.
Contained By:	Masters Abstracts International83-03.
標題:	Computer engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28413534
ISBN:	9798538155033

Prediction of Residual Stress and Distortion in Laser Powder Bed Fusion Additive Manufacturing.
Kosaraju, Bhanuprakash Sairam.

Prediction of Residual Stress and Distortion in Laser Powder Bed Fusion Additive Manufacturing. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 74 p.

Source: Masters Abstracts International, Volume: 83-03.

Thesis (M.S.)--University of South Carolina, 2021.

This item must not be sold to any third party vendors.

Additive Manufacturing (AM) has its proven advantages to unlock the design space and manufacturing capabilities for complex geometries with lightweights. Distortion is one of the most common defects that occur in Laser Powder Bed Fusion Additive Manufacturing (LPBFAM), which is caused by the significant residual stress during the printing process. This can lead to numerous process iterations to achieve the requisite form and fit tolerances.In this study, Finite Element (FE) model that utilizes the element birth approach was developed to predict the residual stress and distortion in the LPBFAM process. The methodology leverages a simplified approach where the detailed scanning pattern with motion of microscale melt is supplanted by slice-by-slice activation. In the model, each mesh layer (slice) consists of one or multiple actual build layers (actual powder thickness). The model successively activates each mesh layer one at a time with an activation time and calculated body heat flux corresponding to the real fabrication process. This multiple layer activation approach yields great computational efficiency while substantially capturing the transient physics of the process. A benchmark case published by NIST, which documented the detailed distortion profile for a bridge geometry, was simulated by this model. The predicted residual stress and distortion were compared against the published experimental data, where good agreement was achieved. In addition, the predictions were also compared with the AM Modeler, an embedded commercial package for AM process modeling in Abaqus. The pros and cons for different methodology were discussed. To further utilize the developed FE model, a thin plate with multiple mini channels was predicted to understand its distortion during the printing process. Lastly, since the methodology is general and it can be applied to other materials systems and AM methods that employ similar fabrication procedure, the distortion in a dog-bone geometry with PLA plastic in Fused Filament Fabrication process was demonstrated to conclude this study.This work sets a solid foundation to continuously develop a robust computational model to mitigate distortion through the optimization of scanning paths based on critical geometry features and the overall thermal characteristics during LPBFAM process. It will be a key component in a suite of numerical tools that enable virtually guided certification for LPBFAM process.

ISBN: 9798538155033Subjects--Topical Terms:

569006
Computer engineering.
Subjects--Index Terms:

3 D Printing

Prediction of Residual Stress and Distortion in Laser Powder Bed Fusion Additive Manufacturing.
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520 $a Additive Manufacturing (AM) has its proven advantages to unlock the design space and manufacturing capabilities for complex geometries with lightweights. Distortion is one of the most common defects that occur in Laser Powder Bed Fusion Additive Manufacturing (LPBFAM), which is caused by the significant residual stress during the printing process. This can lead to numerous process iterations to achieve the requisite form and fit tolerances.In this study, Finite Element (FE) model that utilizes the element birth approach was developed to predict the residual stress and distortion in the LPBFAM process. The methodology leverages a simplified approach where the detailed scanning pattern with motion of microscale melt is supplanted by slice-by-slice activation. In the model, each mesh layer (slice) consists of one or multiple actual build layers (actual powder thickness). The model successively activates each mesh layer one at a time with an activation time and calculated body heat flux corresponding to the real fabrication process. This multiple layer activation approach yields great computational efficiency while substantially capturing the transient physics of the process. A benchmark case published by NIST, which documented the detailed distortion profile for a bridge geometry, was simulated by this model. The predicted residual stress and distortion were compared against the published experimental data, where good agreement was achieved. In addition, the predictions were also compared with the AM Modeler, an embedded commercial package for AM process modeling in Abaqus. The pros and cons for different methodology were discussed. To further utilize the developed FE model, a thin plate with multiple mini channels was predicted to understand its distortion during the printing process. Lastly, since the methodology is general and it can be applied to other materials systems and AM methods that employ similar fabrication procedure, the distortion in a dog-bone geometry with PLA plastic in Fused Filament Fabrication process was demonstrated to conclude this study.This work sets a solid foundation to continuously develop a robust computational model to mitigate distortion through the optimization of scanning paths based on critical geometry features and the overall thermal characteristics during LPBFAM process. It will be a key component in a suite of numerical tools that enable virtually guided certification for LPBFAM process.
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