Prediction of cooling rates based on integrated scanning strategies with sophisticated parametric modeling-assisted simulation for additive manufacturing
摘要
Scanning strategies in laser beam powder bed fusion play a crucial role in determining the resultant micro-structure, thermal gradients, surface quality, and mechanical properties of the fabricated components. Despite their critical importance, the optimization and implementation of these strategies remain constrained by several factors. One significant issue is the lack of customization, as many environments are proprietary and not open-source, limiting the ability to understand, tailor and enhance strategies according to specific requirements. Additionally, integrating thermal simulations with developed approaches is limited due to the absence of a direct link between scanning strategy environments and thermal simulation methods. In this paper, transient thermal analyses were performed utilizing parametric modeling-assisted simulation framework. In this way, two distinct cooling rates (solidification and solid cooling rates) were calculated, which are important for micro-structure and mechanical properties, respectively. To validate the developed framework, we have utilized studies from the literature, experimental measurements of melt pool dimensions, and micro-structure observations obtained through the integration of the framework with Potts Kinetic Monte Carlo method. The average cooling rates for each strategy were examined. The results clearly demonstrate that the different scanning strategies significantly alter the average and distribution of both solidification and solid cooling rates. Compared to the raster unidirectional strategy, the island and bi-directional strategies reduced the average solidification and solid cooling rates by up to 18 and 20%, respectively. On the other hand, interleaved strategies nearly doubled the cooling rates. The island scanning strategy stands out as it reduced the standard deviations of solidification and solid cooling rates by 42 and 60%, respectively, indicating a much more uniform distribution. Finally, we demonstrated a clear correlation between the spatial distribution of cooling rates and the evolution of the micro-structure.