Accelerating High-Fidelity Thermal Process Simulation of Laser Powder Bed Fusion via the Computational Fluid Dynamics Imposed Finite Element Method (CIFEM)
Seth Strayer, William J. Frieden Templeton, Florian Dugast, Sneha Prabha Narra, Albert C. To
Abstract
The current work proposes a finite element method (FEM) to accelerate scanwise thermal process simulation of the laser powder bed fusion (L-PBF) process with computational fluid dynamics (CFD) resolution near the melt pool. Termed the CFD imposed FEM (CIFEM), the transient thermal fields from a high-fidelity CFD simulation and inferred by deep learning are imposed as temperature values rather than utilizing a conventional heat source model as in existing FEM-based process simulations. These fields are enforced only within a relatively small computational region encompassing the melt pool, while heat diffusion effects elsewhere are solved via the FEM. For a wide range of laser power and scan speeds covering the conduction, transition, and keyhole melting regimes, 29 of the 30 total CIFEM-simulated melt pool sizes lie within two standard deviations of the experimental melt pool sizes. Compared with the CFD simulations, the thermal fields obtained by CIFEM possess 7.44% mean absolute relative error (MARE), significantly less than the 43.76% MARE on three representative test cases simulated using the Goldak heat source model calibrated to the measured melt pool dimensions. In terms of computational efficiency, the CIFEM model running on a GPU card with 4,608 Compute Unified Device Architecture (CUDA) cores is 28.2× more efficient than the CFD simulations running on 24 CPU cores in parallel.