Benchmarking advanced multiphase field modeling of Inconel 625 in additive manufacturing: Correlating powder bed fusion with dendrite growth and crack formation

This study provides a comprehensive thermomechanical simulation framework and mapping for the Powder Bed Fusion (PBF) process, with a primary focus on melt pool characterization. It also correlates the cooling behavior to the dendrite growth and some induced imperfections, such as crack evolution that stem from segregation at the grain boundaries. Utilizing the Allen-Cahn phase field formulation combined with an elastoplastic material model based on J2 plasticity, simulations are conducted within the finite element structure of the Multi-physics Object-Oriented Simulation Environment (MOOSE). An adaptive mesh refinement (AMR) strategy ensures precise modeling of the solidification front and powder melting during the interaction between the laser heat source and the powder. Key insights are gained from simulations of Inconel 625 thin plates and benchmarks, exploring the effects of temperature and phase changes on melt pool dimensions. A multi-application framework is developed to automatically transfer the temperature and cooling rate behavior of a representative part to the solidification application. The research addresses critical challenges in PBF, such as liquation cracking, and introduces a novel approach for information transfer between parent and child models, particularly for dendrite growth in a surrogate Ni-Nb-Al ternary system. This transfer incorporates solidification data, including temperature gradients and cooling velocities, enabling detailed predictions of low melting phase-induced liquation cracks. Experimental validation through single-track laser melting on Inconel 625 demonstrates reasonable alignment between melt pool dimensions obtained from simulations and experiments under various laser power and scan speed conditions. Additional phase-field simulations predict microstructural segregation and cellular features along melt pool boundaries under changing solidification dynamics, further enriched by the first phase-field model at the melt pool scale. By integrating computational modeling, experimental validation, and multiscale analysis, this work advances the understanding of PBF processes and additive manufacturing, offering insights into melt pool behavior, defect mitigation, and microstructure development. • Develop the multiplication in the Multi-Physics Object-Oriented Simulation Environment (MOOSE) to transfer information from the macro phase-field and process modeling scale to the micro phase-field modeling, enabling the prediction of the dendrite structure. • Proposes a macroscale thermo-mechanical-phase-field model for the powder bed fusion (PBF) process, aiming to accurately predict melt pool shapes by incorporating coupled phenomena, enhanced with an adaptive mesh refinement (AMR) technique. • Develops a microscale thermo-mechanical–chemical and phase-field framework as a sub-application to study microstructure evolution, including dendrite growth in ternary alloys (e.g., Ni–Nb–Al). • Studies the critical role of process parameters, such as laser power and scanning speed, in determining cooling rates during dendrite formation. • Highlights the critical influence of cooling rates, rather than temperature gradients, on defect formation (e.g., liquation cracks), thereby enhancing PBF part integrity.