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-fluids engineering. Our current research includes:

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

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

Teaching:

• Autumn Semester 2017 - 2023: Fluids Engineering and Turbulence  
• Autumn Semester 2022: Fluids and Data-driven Engineering 
• Autumn Semester 2017 - 2022: Fluid Dynamics 
• Spring Semester 2022: Numerical Analysis for Engineers
• Autumn Semester 2018 - 2019: Physics of the Atmosphere and Wind Energy