Project description
New models to accurately predict laminar to turbulent transition
Modelling turbulent flows using computational fluid dynamics has progressed rapidly over the last decades and given rise to significant changes in the design processes of aircraft, cars and ships. New models are needed to enhance prediction of the laminar flow transition to turbulence for better control of the fluid flow. Against this backdrop, the EU-funded HIFI-TURB project will use high-fidelity large-eddy simulations and direct numerical simulations to predict complex flows. New artificial intelligence and machine learning algorithms will allow researchers to identify important correlations between turbulent quantities. Improved models for complex fluid flows will offer the potential of further reducing energy consumption, emissions and noise of aircraft, ships and cars.
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- engineering and technology mechanical engineering vehicle engineering aerospace engineering aircraft
- natural sciences physical sciences classical mechanics fluid mechanics fluid dynamics
- natural sciences mathematics applied mathematics statistics and probability
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.3.4. - SOCIETAL CHALLENGES - Smart, Green And Integrated Transport
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
RIA - Research and Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MG-2018-2019-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1170 Bruxelles / Brussel
Belgium
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