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HIGH-FIDELITY LES/DNS DATA FOR INNOVATIVE TURBULENCE MODELS

Objective

The most significant challenge in applied fluid dynamics (covering aerospace, energy and propulsion, automotive, maritime industries, chemical process industries) is posed by a lack of understanding of turbulence-dependent features and laminar-to-turbulent transition. As a consequence, the design and analysis of industrial equipment cannot be relied upon to be accurate in challenging flow conditions. Improving the capabilities of models for complex fluid flows, offers the potential of reducing energy consumption of aircraft, cars, and ships, with consequent reduction in emissions and noise of combustion-based engines The inevitable result is a major impact on economical and environmental factors as well as on economy, industrial leadership in the highly competitive global position. Hence, the ability to understand, model and predict turbulence and transition phenomena is the key requirement in the design of efficient and environmentally acceptable fluids-based energy transfer systems. Against this background, the present proposal sets out a highly ambitious and innovative program of work designed to address some influential deficiencies in advanced statistical models of turbulence. The program rests on the following pillars of excellence: • The exploitation of high-fidelity LES/DNS data for a range of -reference flows that contain key flow features of major interest • The application of novel artificial intelligence and machine-learning algorithms to identify significant correlations between representative turbulent quantities • The guidance of the research towards improved models by four world-renown industrial and academic experts in turbulence. The consortium is formed by major industrial aeronautical companies and software editor, an SME acting as coordinator, well-known research centra and academic groups, including ERCOFTAC, acting as a source of turbulence expertise and as a repository for the generated data, to be made openly available.
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Coordinator

NUMERICAL MECHANICS APPLICATIONS INTERNATIONAL SA

Address

Chaussee De La Hulpe 187-189
1170 Bruxelles

Belgium

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

EU Contribution

€ 510 000

Participants (14)

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DASSAULT AVIATION

France

EU Contribution

€ 276 750

SAFRAN SA

France

EU Contribution

€ 213 877,50

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

United Kingdom

EU Contribution

€ 296 497,50

ANSYS GERMANY GMBH

Germany

EU Contribution

€ 50 937,50

CINECA CONSORZIO INTERUNIVERSITARIO

Italy

EU Contribution

€ 251 875

BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION

Spain

EU Contribution

€ 237 812,50

CENTRE DE RECHERCHE EN AERONAUTIQUE ASBL - CENAERO

Belgium

EU Contribution

€ 305 625

CENTRE EUROPEEN DE RECHERCHE ET DE FORMATION AVANCEE EN CALCUL SCIENTIFIQUE

France

EU Contribution

€ 299 875

OFFICE NATIONAL D'ETUDES ET DE RECHERCHES AEROSPATIALES

France

EU Contribution

€ 281 206,25

DEUTSCHES ZENTRUM FUER LUFT - UND RAUMFAHRT EV

Germany

EU Contribution

€ 308 185

UNIVERSITA' DEGLI STUDI DI BERGAMO

Italy

EU Contribution

€ 250 000

UNIVERSITE CATHOLIQUE DE LOUVAIN

Belgium

EU Contribution

€ 258 318,75

ERCOFTAC EUROPEAN RESEARCH COMMUNITY ON FLOW TURBULENCE AND COMBUSTION

Belgium

EU Contribution

€ 312 500

FEDERAL STATE UNITARY ENTERPRISE THE CENTRAL AEROHYDRODYNAMIC INSTITUTE NAMED AFTER PROF. N.E. ZHUKOVSKY

Russia

Project information

Grant agreement ID: 814837

Status

Ongoing project

  • Start date

    1 July 2019

  • End date

    30 June 2022

Funded under:

H2020-EU.3.4.

  • Overall budget:

    € 3 853 460

  • EU contribution

    € 3 853 460

Coordinated by:

NUMERICAL MECHANICS APPLICATIONS INTERNATIONAL SA

Belgium