An Efficient Track-Scale Model for Laser Powder Bed Fusion Additive Manufacturing: Part 2—Mechanical Model

Abstract

This is the second of two manuscripts that presents a computationally efficient full-field deterministic model for laser powder bed fusion (LPBF). The Hybrid Line (HL) thermal model developed in part I is extended to predict the in-process residual stresses due to laser processing of a nickel-based superalloy, RENÉ 65. The computational efficiency and accuracy of the HL thermo-mechanical model is first compared to the exponential decaying heat input model on a single-track simulation. LPBF thin-wall builds with three different laser powers and four printing patterns are evaluated in this study and compared with part-scale simulations. The simulations show good agreements with the experimental X-Ray diffraction measured residual stresses. Compared to the laser power, the scanning pattern is demonstrated to have significant effects on residual stresses. Laser scan patterns utilizing short laser paths generate lower tensile stress along the longitudinal direction of the part and higher compressive stress along the build direction.

Buckling Mechanism Simulation for Thin-Wall Components Made by Laser Powder Bed Fusion

“…Each component had different part lengths -40 mm for component 1 and 60 mm for component 2. Part length affects the residual stresses and part buckling [16]. Both components were built until excessive distortion led to part failure.…”

“…The outer surface of the geometry is subjected to radiation and convection to replicate the heat lost during the process. The hybrid line heat input model is used to integrate the exponentially decaying heat input model over increment time [21,22]. The lumping technique is used to group the layers and heat inputs, which enhances the computational efficiency of the model.…”

“…The buckling simulation is restricted to buckling under uniaxial pressure. The external pressure mimics the effect of created residual stress in the Z-direction (or build direction -BD), which plays a major role in part failure [16]. The critical state is analyzed by solving a linear eigenproblem based on the system's minimal potential energy, according to the delimited approach to bifurcation stability loss [23].…”

Review of Multiscale Modeling and Simulation Techniques in Metal Forming, Bending, Welding, and Casting Processes for Enhanced Predictive Design and Analysis

“…For example, in metal deformation, MD simulations can provide insights into dislocation motion, grain boundary behavior, and the mechanical response of the material under different loading conditions. By tracking the atomic trajectories, MD simulations can elucidate the atomistic mechanisms governing plastic deformation, crack propagation, and other deformation-related phenomena [44]. Density functional theory (DFT) calculations are based on quantum mechanics principles and provide a more accurate description of electronic properties and interactions at the atomic scale.…”

Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing

“…Considering the limits of in situ characterization techniques in LPBF involving limited spatial resolution, difficulties in capturing complex three-dimensional structures, and high cost, computational models that simulate the melt pool dynamics by using Computational Fluid Dynamics (CFD) to account for the fluid flow, heat transfer, and phase change within the melt pool have been applied to interpret the experimental data and assist the process development [31][32][33][34][35][36][37][38][39]. During this process, physical forces, including surface tension, viscous forces, recoil pressure, and gravity, interact within the molten pool and influence material flow and heat transfer [16,[40][41][42][43][44][45].…”