Island scanning pattern optimization for residual deformation mitigation in laser powder bed fusion via sequential inherent strain method and sensitivity analysis

2021 ◽  
pp. 102116
Author(s):  
Qian Chen ◽  
Hunter Taylor ◽  
Akihiro Takezawa ◽  
Xuan Liang ◽  
Xavier Jimenez ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Residual Deformation ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Scanning Pattern ◽  
Inherent Strain ◽  
Inherent Strain Method ◽  
Strain Method

Numerical Prediction of Residual Deformation and Failure for Powder Bed Fusion Additive Manufacturing of Metal Parts

2020 ◽  
Vol 36 (5) ◽  
pp. 623-636
Author(s):  
D.D. Lyu ◽  
W. Hu ◽  
B. Ren ◽  
X.F. Pan ◽  
C. T. Wu
Keyword(s):  
Additive Manufacturing ◽  
Process Simulation ◽  
Residual Deformation ◽  
Numerical Approach ◽  
Small Scale ◽  
Powder Bed Fusion ◽  
Failure Characteristics ◽  
Deformation And Failure ◽  
Powder Bed ◽  
Inherent Strain Method

ABSTRACTResidual deformation and failure are two critical issues in powder bed fusion (PBF) additive manufacturing (AM) of metal products. Residual deformation caused by the non-uniform residual stress distribution dramatically affects the quality of AM product and can result in catastrophic failure in operation. Therefore, the development of an effective numerical approach to predict residual deformation and failure characteristics of AM product is always a major concern in industrial applications.In this paper, a numerical approach in predicting residual distortion, stress and failure in AM products is presented. The conventional inherent strain method used in welding process is modified to consider the specific characteristic of AM process, such as the influences of reheating and scanning pattern. This approach consists of three simulation steps including a detailed process simulation in small-scale, a onetime static mechanical finite element analysis in part-scale, and a material failure analysis. First, the inherent strains are calculated from a thermo-mechanical process simulation in small-scale, which considers AM process parameters, such as laser power, scanning speed and path. The physical state in deposited materials including powder, liquid and solid states are taken into account in the simulation by specifying the solidus and liquidus temperature and corresponding material properties. Then the inherent strains are applied layer by layer to the part-scale simulation, where the residual distortion and stress can be predicted efficiently. Finally, a Lagrange particle method is utilized to study the failure characteristics of AM products. Numerical examples are studied to investigate the effectiveness and applicability of present approach.

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