Project start: 1.10.2025.

Computational Fluid Dynamics (CFD) enables the examination of complex phenomena in both micro and macro systems. These simulations are highly computationally demanding and typically require supercomputers. This project aims to improve three key areas in micro and macro systems through CFD simulations by establishing a more rational approach to numerical studies that integrates artificial intelligence (AI). The selected research areas show uneven levels of technical advancement. Therefore, through interdisciplinary knowledge transfer, significant scientific contributions to CFD in these domains are expected. In response to the need for flexible electricity production in hydroelectric power plants, the influence of geometric parameters of water turbines on efficiency across a broader operating range will be examined. Additionally, the ecological impacts of these parameters will be considered. Another focus is the hydrodynamics of vessels. CFD allows the study of Parametric Rolling Movement (PRM), caused by adverse combinations of environmental, operational, and design parameters. By optimizing the hull in the early design phase, PRM can be avoided. CFD will also be used for further hull optimization to minimize hydraulic losses and reduce cavitation on the propeller. Furthermore, a multidisciplinary approach enables the application of CFD in biomedicine, particularly in the study of endodontic tooth irrigation. Modern CFD models can be developed using real tooth root scans obtained through micro-computed tomography (CT), in contrast to previous studies that relied on idealized models of endodontic spaces. Combined with the optimization of geometric and irrigation parameters, CFD can enhance scientific understanding of irrigation techniques and support their clinical application. Finally, machine learning methods will be integrated into each optimization process to reduce computational demands and speed up simulation times.