Abstract

Finite Element Analysis (FEA) is used to predict the transient thermal cycle and optimize process parameters to analyze these effects on deformation and residual stresses. However, the process of predicting the thermal history in this process with the FEA method is usually time-consuming, especially for large-scale parts. In this paper, an effective predictive model of part deformation and residual stress was developed for accurately predicting deformation and residual stresses in large-scale parts. An equivalent body heat flux proposed from the single layer laser scan model was imported as the thermal load to the layer by layer model. The hatched layer is then heated up by the equivalent body heat flux and used as a basic unit element to build up the macroscale part. The thermal history and residual stress fields of two solid parts with different support structures during the SLM process were simulated. Layer heat source method has the capability for fast temperature prediction in the SLM process, while sacrificing modeling details for the computational time-saving purpose. Thus numerical modeling in this work can be a very useful tool for the parametric study of process parameters, residual stresses and deformations.

Meeting Name

25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 (2020: Aug. 9-14, Chicago, IL)

Department(s)

Mechanical and Aerospace Engineering

Research Center/Lab(s)

Center for Research in Energy and Environment (CREE)

Keywords and Phrases

Distortion; Finite element analysis; Layer heat source model; Residual stress; SLM

International Standard Serial Number (ISSN)

2351-9789

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2019 The Authors, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Date

01 Aug 2019

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