Håkan Nilsson

Håkan Nilsson is a Full Professor in Fluid Dynamics at Chalmers University of Technology. His research focuses on computational fluid dynamics (CFD) with applications in hydropower systems, particularly turbine flow analysis, cavitation modeling, and generator cooling air dynamics. He utilizes OpenFOAM for numerical simulations and develops advanced algorithms for mesh deformation and flow control.

• Academic Rank: Full Professor
• Institution: Chalmers University of Technology
• Primary Research: Hydropower Turbines, Cavitation, CFD, Machine Learning, Multiphase Flow

His recent work integrates machine learning with CFD for optimizing turbine operations and predictive maintenance in hydropower plants. Key projects include ALPHEUS and investigations into contra-rotating pump-turbine systems for low-head energy storage. Collaborations span experimental validation with experts in PIV, laser Doppler velocimetry, and industrial partners in renewable energy.

Research trends highlight 15+ years of publications on turbulence modeling, vortex dynamics, and fluid-structure interaction in hydraulic systems. Sub-fields include Francis turbine transients, Kaplan turbine rotor-stator interactions, and applications in biomedical fluid dynamics and welding processes. Scientific awards are not explicitly mentioned.