The need to reduce the skin-friction drag of aerodynamic vehicles is of paramount importance. Nominally 50% of the total energy consumption of an aircraft or high-speed train is due to skin-friction drag. Reducing skin-friction drag reduces fuel consumption and transport emissions, leading to vast economic savings and wider health and environmental benefits. In this project, wall-normal blowing is combined with a Bayesian Optimisation framework in order to find the optimal parameters to generate net energy savings over a turbulent boundary layer. It is found that wall-normal blowing with amplitudes of less than 1% of the freestream velocity of the boundary layer can generate a drag reduction of up to 80% with up to 5% of energy saving.
Read the complete user research report at the Gauss Centre for Supercomputing.
Imperial College London, United Kingdom
Computational & Scientific Engineering
All User Research Reports
High-Performance Computing Center Stuttgart
Nobelstraße 19, 70569 Stuttgart, Germany
+49 (0) 711 / 685-87 209
A member of the Gauss Centre for Supercomputing, HLRS is one of three German national centers for high-performance computing.
HLRS is a central unit of the University of Stuttgart.