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The objective of this work is to predict a type of thermal-induced process failure called recoater crash that occurs frequently during laser powder bed fusion (LPBF) additive manufacturing. Rapid and accurate thermomechanical simulations are valuable for LPBF practitioners to identify and correct potential issues in the part design and processing conditions that may cause recoater crashes. In this work, to predict the likelihood of a recoater crash (recoater contact or impact) we develop and apply a computationally efficient thermomechanical modeling approach based on graph theory. The accuracy and computational efficiency of the approach is demonstrated by comparison with both non-proprietary finite element analysis (Abaqus), and a proprietary LPBF simulation software (Autodesk Netfabb). Based on both numerical (verification) and experimental (validation) studies, the proposed approach is found to be 5 to 6 times faster than the non-proprietary finite element modeling and has the same order of computational time as a commercial simulation software (Netfabb) without sacrificing prediction accuracy.
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This content will become publicly available on November 13, 2026
SmartScan 2.0: An Intelligent Scanning Approach for Reduced Residual Stress and Deformation in LPBF Using a Coupled Linear Thermoelastic Model
Laser powder bed fusion (LPBF) enables fabrication of complex metal components but remains limited by residual stress accumulation and part deformation. Most existing scan sequence generation strategies for LPBF rely on heuristic rules or empirical optimizations that are suboptimal, difficult to generalize across geometries, and insensitive to the underlying physics of the problem. The SmartScan framework was developed to overcome these limitations through model-based and optimization-driven scan sequence generation. SmartScan 1.0 employed a thermal model to optimize temperature uniformity, leading to significant reductions in residual stress and distortion compared to state-of-the-art heuristic approaches. However, its formulation ignored the mechanical aspects of residual stress and deformation. To address this deficiency, a preliminary study introduced SmartScan 2.0 (Pre) which utilized a decoupled linear thermomechanical formulation for scan sequence optimization for 2D geometries. Building on this foundation, this paper proposes SmartScan 2.0 based on a sequentially coupled linear thermoelastic model that simultaneously solves temperature and displacement fields to minimize thermally induced elastic deformation in 3D geometries. The computational efficiency of SmartScan 2.0 is enhanced through nondimensional scaling. Experimental validation on 3D LPBF specimens shows that SmartScan 2.0 achieves up to 69.0% reduction in residual stress and 17.4% reduction in deformation relative to SmartScan 1.0, and up to 60.6% reduction in residual stress and 12.8% reduction in deformation compared with SmartScan 2.0 (Pre). This work establishes the superiority of scan sequence optimization using coupled linear thermomechanical models over the existing thermal-only or decoupled thermomechanical approaches, without significantly sacrificing computational efficiency.
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- Award ID(s):
- 2430109
- PAR ID:
- 10648961
- Publisher / Repository:
- Preprints.org
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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