Summary
A century of exhaustive turbulence research has allowed the development of a wide range of turbulence closure models, analytical parametrisations and scaling laws, which enter virtually all design and modelling protocols that involve high Reynolds number flows. Closer inspection, however, reveals that only two extreme and polar-opposite turbulence regimes have been well-understood and modelled. When turbulence is highly-strained and evolves rapidly, or when it is lowly-strained and evolves slowly. The in-between regime of intermediate strain, perhaps the most relevant for engineering and environmental applications, remains obscure.
This proposal is about developing and validating a theory for the intermediate-strain turbulence regime, based on the conjecture that it is governed by a universal flow-behaviour, termed ‘rapid self-similarity’, which combines elements from both the high- and low-strain regimes. The proposed investigation is based on three developments. 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.
This proposal is about developing and validating a theory for the intermediate-strain turbulence regime, based on the conjecture that it is governed by a universal flow-behaviour, termed ‘rapid self-similarity’, which combines elements from both the high- and low-strain regimes. The proposed investigation is based on three developments. 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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101163321 |
| Start date: | 01-01-2025 |
| End date: | 31-12-2029 |
| Total budget - Public funding: | 1 498 820,00 Euro - 1 498 820,00 Euro |
Cordis data
Original description
A century of exhaustive turbulence research has allowed the development of a wide range of turbulence closure models, analytical parametrisations and scaling laws, which enter virtually all design and modelling protocols that involve high Reynolds number flows. Closer inspection, however, reveals that only two extreme and polar-opposite turbulence regimes have been well-understood and modelled. When turbulence is highly-strained and evolves rapidly, or when it is lowly-strained and evolves slowly. The in-between regime of intermediate strain, perhaps the most relevant for engineering and environmental applications, remains obscure.This proposal is about developing and validating a theory for the intermediate-strain turbulence regime, based on the conjecture that it is governed by a universal flow-behaviour, termed ‘rapid self-similarity’, which combines elements from both the high- and low-strain regimes. The proposed investigation is based on three developments. 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.
Status
SIGNEDCall topic
ERC-2024-STGUpdate Date
25-11-2024
Images
No images available.
Geographical location(s)
Search
