SOURCE-LINKED INTELLIGENCE

Beyond self-similarity in turbulence

CORDIS · observation · Publication date unknown

s. First, the accumulation of evidence in the literature that intermediate-strain turbulence dynamics may accept an analytical description known as the new dissipation law. Second, the development of machine learning techniques which allow the extraction of physical insights directly from data. Third, the attainment of mature experimental and numerical simulation methods in fluid mechanics, capable of resolving the spatio-temporal properties of turbulent flows. The impact of ONSET is potentially very high, as it will improve the understanding and modelling of a wide range of applications of engineering and environmental science connected to intermediate-strain turbulence. ONSET will demonstrate that by focusing on two example applications: improvement of wind energy harvesting via enhanced wind farm flow modelling, and increase of Unmanned Aerial Vehicle flight efficiency and duration, by making use of UAV group aerodynamics. Turbulence theory, Experimental fluid mechanics

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recordType

award

status

SIGNED

region

EU

value

1498820

unit

EUR