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Computational Framework to Evaluate the Relationships between Process Parameters, Grain Structure and Mechanical Properties of Additive Manufactured Materials

Subject Area Mechanical Properties of Metallic Materials and their Microstructural Origins
Metallurgical, Thermal and Thermomechanical Treatment of Materials
Thermodynamics and Kinetics as well as Properties of Phases and Microstructure of Materials
Term from 2017 to 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 388878396
 
Final Report Year 2022

Final Report Abstract

This project aimed to develop and employ a computational method to simulate grain structure and texture evolution during Powder Bed Fusion - Laser Beam (PBF-LB) production of aluminum specimens. A 3D Cellular Automata (CA) model was developed to simulate solidified microstructures caused by a moving heat source simulated using the Finite Difference (FD) method. The coupled CAFD tool was optimized for efficient simulations including several hatches and layers (representative volume > 1 mm3). While the CAFD simulation of grain growth was capable of producing common columnar grains and texture components, it was unable to replicate the bimodal grain structures found in Al alloys such as AlSi10Mg and Scalmalloy®, where fusion boundary nucleation plays an essential role. It was found that the standard nucleation model does not account for this unique phenomenon, since it results in equiaxed grains at the center of the melt pool. Therefore, particle-based nucleation models were established and implemented into the CAFD simulation of these alloys. Consequently, the main grain structure and texture characteristics (fusion boundary nucleation in both alloys, epitaxial growth at the melt pool bottom of AlSi10Mg, and texture component of <001> build-direction in columnar grains) were successfully delivered by the CAFD approach powered by the particle-based nucleation model with the nucleation incubation criterion. The method was then enhanced by including a multi-scale and solidification-aware thermal analysis to account for intrinsic preheating and the proper release of the latent heat of fusion. A CA pore distributor tool was also developed to explicitly introduce multiple pore shapes and distributions based on the measured porosity. Meanwhile, the significance of eutectic Si particles has been identified. Therefore, in addition to the numerical CA simulation, an analytical solidification analysis was established to predict solidification features such as growth kinetics, microsegregation, solid/liquid interface mode, and percentage and composition of the eutectic phase as a function of process parameters.

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