Project description
Predicting the convective turbulence of extreme weather events to protect wind turbines
Mathematical models help us understand and even predict the workings of the world around us. Foreseeing certain events can lead to better management of them. When it comes to the tremendous turbulent kinetic energy that buffets wind turbines during atmospheric extreme weather events, like hurricanes and heat waves, we are currently missing much needed predictive foresight about how that energy is dissipated. The EU-funded ConvExt project will develop the mathematical foundations that will shed light on the formation of extreme energy events, eventually enabling their prediction. The project will use advanced experimental measurements to develop data-driven tools that predict extreme events and enable us to meet their unique challenges.
Objective
Wind storms, hurricanes, and heat waves, are atmospheric extreme events with a huge societal impact and significant economic costs. Thus, their correct identification is important, e.g. for off-shore wind power generation. This project is a fundamental study on hydrodynamics turbulence, whose results will provide a methodological basis for innovation in wind energy technology. Extreme atmospheric convection events are characterized by large local amplitudes of the rate at which turbulent kinetic energy is dissipated, a central quantity that cannot be predicted from the highly nonlinear mathematical equations of fluid motion. This project aims at understanding the formation and predicting such extreme events of energy dissipation in Rayleigh-Bénard convection (RBC), a paradigm for atmospheric motion. Advanced high resolution measurements of the small-scale velocity field and its gradients will therefore be performed in a pressurized convection chamber at TU Ilmenau which allows to downscale turbulence and to use Particle Image Velocimetry for flows at Rayleigh numbers up to a million or higher. By combination of measured kinetic energy dissipation rate in the bulk and wall shear stresses in the boundary layer, we will identify the advection patterns that generate the extreme dissipation events. The present experimental analysis will be complemented by existing training data records of high-resolution direct numerical simulations of the same flows. They serve to develop data-driven methods and algorithms, such as recurrent neural networks, to predict such extreme events in experimental analyses. The goal of this project is to advance our understanding of the dynamic evolution of such extreme events in a RBC flow and to develop reliable tools to predict the events. This research objective will be reached in a multidisciplinary way by a combination of high resolution optical flow measurements with the data-driven modeling and data analytics by machine learning.
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.
- engineering and technology environmental engineering energy and fuels renewable energy wind energy
- natural sciences mathematics applied mathematics numerical analysis
- natural sciences computer and information sciences software software applications simulation software
- natural sciences physical sciences optics laser physics
- natural sciences mathematics applied mathematics mathematical model
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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.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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-MSCA-IF-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.
98693 Ilmenau
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.