Dong, Wen
(2024)
New Developments in Inherent Strain Method for Predicting and Mitigating Residual Stress and Distortion in Metal Additive Manufacturing.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
As an additive manufacturing process for fabricating metal components, laser powder bed fusion (L-PBF) and wire-arc directed energy deposition (wire-arc DED) have drawn increasing attention in the past few decades due to their advantages such as fast production, high customization, and waste reduction. During fabrication, the rapid, intense, and repeated heat input (laser beam or wire arc) leads to a complex thermal history in parts, resulting in significant residual stress and distortion. These residual stress and distortion can adversely affect product quality by increasing surface roughness, reducing dimensional accuracy, and introducing defects into the parts.
This dissertation is focused on improving the inherent strain (IS) method for predicting residual stress and deformation in parts manufactured by L-PBF and wire-arc DED processes. In addition, two frameworks based on the IS method for recoater interference prediction and distortion compensation in L-PBF are proposed. Chapter 2 introduces a new procedure for implementing the modified inherent strain (MIS) method. This procedure incorporates an additional solution step that uses mechanical properties at elevated temperatures, markedly improving the accuracy of the MIS method on residual stress prediction. Chapter 3 extends the MIS method to include the heat accumulation effect in the wire-arc DED process. This enhancement involves introducing a flashing heating simulation to calculate interpass temperature and applying temperature-dependent ISs in the MIS-based simulation. In Chapter 4, an integrated simulation and experimental framework for predicting potential recoater interference in the L-PBF process is proposed. This framework addresses the previously undefined criterion for recoater interference and incorporates the edge effects when calculating the part deformation. In Chapter 5, a data-driven distortion compensation framework for the L-PBF process is presented. The framework employs a Gaussian process regression (GPR) model and reduced-order modeling to learn from experimentally-validated IS simulation data and generate the compensated shape.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
3 June 2024 |
| Date Type: |
Publication |
| Defense Date: |
16 January 2024 |
| Approval Date: |
3 June 2024 |
| Submission Date: |
23 January 2024 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
204 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Mechanical Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Additive manufacturing; Inherent strain method; Residual stress and deformation; Numerical simulation |
| Date Deposited: |
03 Jun 2024 14:35 |
| Last Modified: |
03 Jun 2024 14:35 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/45754 |
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