A Framework for Simulating the Path-level Residual Stress in the Laser Powder Bed Fusion Process

TL;DR

The paper addresses the computational challenge of predicting path-level residual stress in Laser Powder Bed Fusion by introducing a path-level thermomechanical framework that employs an effective thermal strain to encode anisotropic stresses. The method combines a fine-scale meltpool-derived stress basis with a path-level thermal history from PBF-CAPL to construct the anisotropic strain $m{\epsilon_{t,e}}(T) = \left(\int_{T_m}^{T} \alpha(t) dt\right) [1,r,1,0,0,0]^T$, where $r$ is derived from the ratio of average stresses around the melt pool via $r = \frac{\epsilon_{t,x}}{\epsilon_{t,y}} = \frac{\epsilon_{e,x}}{\epsilon_{e,y}} = \frac{1-\nu (\sigma_y/\sigma_x)}{(\sigma_y/\sigma_x)-\nu}$. This approach enables path-level simulations with coarser discretization while maintaining key anisotropic effects, and is validated against high-fidelity voxel-based results in Ti6Al4V. The authors apply the framework to various island patterns and layer shapes to investigate how path history and boundary conditions influence residual stresses, finding that scanning direction and layer boundaries strongly shape stress distributions. The work offers a scalable route to part-scale LPBF simulations that preserve path-dependent phenomena, with potential implications for process optimization and defect mitigation in additive manufacturing.

Abstract

Laser Powder Bed Fusion (LPBF) additive manufacturing has revolutionized industries with its capability to create intricate and customized components. The LPBF process uses moving heat sources to melt and solidify metal powders. The fast melting and cooling leads to residual stress, which critically affects the part quality. Currently, the computational intensity of accurately simulating the residual stress on the path scale remains a significant challenge, limiting our understanding of the LPBF processes. This paper presents a framework for simulating the LPBF process residual stress based on the path-level thermal history. Compared with the existing approaches, the path-level simulation requires discretization only to capture the scanning path rather than the details of the melt pools, thus requiring less dense mesh and is more computationally efficient. We develop this framework by introducing a new concept termed effective thermal strain to capture the anisotropic thermal strain near and around the melt pool. We validate our approach with the high-fidelity results from the literature. We use the proposed approach to simulate various single-island scanning patterns and layers with multiple full and trimmed islands. We further investigate the influence of the path-level thermal history and the layer shape on the residual stress by analyzing their simulation results.

Figures (13)

• Figure 1: Outline of the path-level LPBF simulation
• Figure 2: The expansion coefficient of Ti6Al4V as a function of temperature.
• Figure 3: PBF-CAPL discretizes the scanning path (in black) into elements (in red). The element width is equal to the hatch distance.
• Figure 4: Scanning paths (unidirectional and alternating with a contour scanning) used by Parry et al. parry2016understanding. The laser start from blue to red. As shown by the color, the post contour scanning happens after the parallel scanning.
• Figure 5: Snapshot of temperature distribution around the melt pool and the fine scale residual stress. The pixel size is 20 $\mu$m. The melt pool length is 0.32 mm. Left: stress along the scanning direction. Right: stress in the transverse direction.