High-Fidelity LES/DNS Data for Innovative Turbulence Models

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 centres 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.


Numerical Mechanics Applications International SA
Chaussee De La Hulpe 187-189
1170 Bruxelles Belgium


Dassault Aviation, France
Safran SA, France
Imperial College of Science Technology and Medicine, United Kingdom
Ansys Germany Gmbh, Germany
Cineca Consorzio Interuniversitario, Italy
Barcelona Supercomputing Center - Bsc, Spain
Centre De Recherche En Aeronautique Asbl - Cenaero, Belgium
Centre Europeen de Recherche et De Formation Avancee en Calcul Scientifique - Cerfacs, France
Office National D'etudes Et De Recherches Aerospatiales - Onera, France
Deutsches Zentrum Fuer Luftund Raumfahrt Ev - Dlr, Germany
Universita' Degli Studi Di Bergamo, Unibg, Italy
Universite Catholique De Louvain, Ucl, Belgium
European Research Community On Flow Turbulence And Combustion - Ercoftac, Belgium
Federal State Unitary Enterprise The Central Aerohydrodynamic Institute Named After Prof. N.E. Zhukovsky - Tsagi, Russian Federation
The Boeing Company Corporation, United States

The NASA TTT-RCA group is participating to the to the HiFi-TURB project as an observer.
The HIFI-TURB project is funded by the EU Horizon 2020 program under Grant Agreement 814837.



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