Author(s): Elina Vargsen

Abstract: Additive manufacturing (AM), commonly known as 3D printing, has emerged as a transformative approach in modern manufacturing owing to its capability for design flexibility, material efficiency, and layer-by-layer fabrication. However, the intrinsic thermal cycles during AM introduce non-uniform heat distribution, which leads to residual stresses, microstructural heterogeneities, and distortions that compromise mechanical integrity. Finite element analysis (FEA) provides a powerful computational framework to simulate transient heat transfer, enabling prediction and optimization of thermal profiles across additively manufactured components. This study explores the state-of-the-art in FEA modeling of heat distribution during AM, integrating computational heat transfer principles with multiphysics approaches. Using benchmark datasets and validated experimental results, transient thermal models were developed in ANSYS Workbench and COMSOL Multiphysics to capture localized temperature gradients and cooling rates across different metallic alloys. Comparative analysis reveals that element type selection, mesh density, and incorporation of laser-material interaction physics significantly affect predictive accuracy. The results demonstrate that Gaussian heat source models replicate experimental melt pool dimensions more accurately than uniform models, while adaptive meshing reduces computational cost by 32%. Furthermore, alloy-specific simulations highlight the critical influence of thermal conductivity and phase transition behavior on heat propagation. The findings reinforce that accurate FEA of heat distribution is essential for defect mitigation and process optimization in AM, offering guidelines for improving predictive reliability and industrial adoption.

Pages: 39-45 | Views: 62 | Downloads: 37

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