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ONSET

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Beyond self similarity in turbulence

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 invo... ver más

31/12/2029

IMPERIAL COLLEGE O...

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

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Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-09-26

ERC-2024-STG: ERC STARTING GRANTS Scope:Objectives

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IMPERIAL COLLEGE OF SCIENCE...

1.50M€ | Lider

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Duración del proyecto: 63 meses Fecha Inicio: 2024-09-26
Fecha Fin: 2029-12-31

Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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