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Fluid Mechanics and Turbulence


The focus of our research is to develop and test improved computer models to predict the complex interaction between turbulent flows and the environment, with emphasis on energy systems. Our mission is to support our industrial partners toward the full green transition and digitalization of society in the area of thermo-fluid engineering. Our current research includes:

  • Computational fluid dynamics (DNS/LES/RANS) with the focus on complex geometry and complex physics (e.g., turbulence, multiphase, reacting flows, and heat transfer) 
  • Data-driven modeling and machine learning for fluid flows
  • Wind-farm modeling and control
  • Uncertainty quantification and robust optimization

Open positions and student projects:

Please contact abkar@mpe.au.dk if you are looking for a MS project. Some example projects are given below. Other projects based on personal preferences can be discussed in person.

  • Project: Wind-farm modeling and control using physics-based and data-driven methods.
  • Project: Turbulence modeling via deep learning.
  • Project: CFD and data-driven modeling of fluid flow with application to Digital Twins.
  • Project: Shape and topology optimization using CFD.
  • Project: CFD simulations of cardiovascular systems.
  • Project: Uncertainty quantification in CFD simulations of turbulent flows.
  • Project: CFD simulations of wind flow in complex terrain and over sea surfaces.


Mahdi Abkar

Head of section of Fluids and Energy, associate professor