Advanced meshless modelling and simulation of microstructure evolution for the top-quality metal products

The microstructure evolution during the casting of metal products significantly impacts the quality of solidified material. Therefore, predicting microstructure evolution is crucial for designing and producing high-quality castings for scientific, medical, and industrial use. This postdoctoral project aims to enhance the physical modelling of the casting, especially the direct-chill casting of aluminium alloys and the continuous casting of steel. The project's primary focus is the upgrade of the already implemented physical models for predicting microstructure evolution during the casting. Another essential aim of the project is upgrading the adaptive meshless solution procedure for accurate and efficient modelling of microstructure evolution. The project represents a logical continuation of the completed applied research projects: L2-6775 Simulation of industrial solidification processes under the influence of electromagnetic fields, L2-9246 Multiphysics and multi-scale numerical modelling for competitive continuous casting, MARTINA Materials and technologies for new applications, MARTIN Modelling thermo-mechanical processing of aluminium alloys for top-most products. The project leader participated in the mentioned completed projects as a PhD student. He co-developed the microscopic and mesoscopic physical models for predicting grain structure's evolution during aluminium alloys and steel casting. The project's first goal is to upgrade the adaptive algorithm for the solution of the phase-field (PF) models. The main philosophy behind the adaptive algorithm is to dynamically ensure the highest space-time resolution at the evolving solid-liquid interface and the lowest resolution in the bulk of phases. That way, we reduce the problem's computational complexity while sustaining accuracy. The meshless 2-D quadtree-based space-time adaptive solution procedure is currently used for PF modelling. The algorithm will be upgraded to 3-D in the framework of the project using the octree-based adaptivity. The project's second goal is to implement a polycrystalline phase-field model for the solidification of metallic alloys. The 2-D cellular automaton model currently simulates polycrystalline solidification. The 2-D PF model will be implemented first, followed by the implementation of the 3-D model. The project's final goal is to incorporate the 3-D polycrystalline PF model into the multi-physics multi-scale simulation system for a detailed prediction of solidification phenomena during the casting of metal products. The system considers mass, momentum, heat, and species conservation equations on the macroscopic scale. The 2-D cellular automaton and PF models apply to simulate microstructure evolution at mesoscopic and microscopic scales. The macroscopic model provides temperature and chemical history to mesoscopic and microscopic models. In the framework of the postdoctoral project, the 3-D PF model will replace the current 2-D mesoscopic and microscopic models. The developed octree-based space-time adaptive algorithm will allow the computationally demanding 3-D PF simulations on the mesoscopic scale to be performed in acceptable computation times. The main originality of the postdoctoral project is in coupling 3-D octree-based and 2-D quadtree-based space-time adaptive algorithms with the local meshless methods for an accurate and computationally efficient PF modelling of polycrystalline dendritic solidification for the first time. This unique numerical approach will represent a state-of-the-art simulation tool for predicting microstructure evolution during the casting of metal products. The project results will be published in high-ranked scientific journals and presented at international conferences in the field of numerical modelling and solidification.