Objective
Fluid-structure interaction (FSI) is a ubiquitous phenomenon in industry such as ocean engineering, biomedicine, aerospace and a driven idea for hydrokinetic energy conversion. Strong nonlinear interactions between flow and structures, as well as turbulent flow bring a huge challenge for understanding and dynamics prediction of the FSI systems. Facing with this challenge and the rising motivation of harnessing clean energy from natural fluids, SMARTFLUIDS aims to build a framework of developing Reduced Order Models (ROMs) with low complexity but retaining dominant physics for FSI, which will bring a deep understanding and efficient prediction of FSI.
A low-dimensional subspace of the FSI will be extracted using modal analysis through Variational Autoencoders (VAE) based on deep learning (DL) of FSI data. The FSI data will be obtained by performing high-fidelity computational fluids dynamics (CFD) simulations of classic FSI problems. The ROMs are developed by both physics-informed mapping of governing equations onto the low-dimensional subspace and data-driven techniques to deal with nonlinear and unresolved parts of the FSI. Physical constrains are incorporated and sparse measurements of the FSI will be used in building the ROMs. Dynamics and future states of the FSI, hydro- or aerodynamic loads on the structures and structural responses can be predicted based on the ROMs. SMARTFLUIDS will provide an innovative and systematic view of FSI by focusing on a few dominant features and enrich the knowledge of FSI physics by adopting latest DL techniques. The project will bring a novel solution to reduce time and cost of CFD and experiments in predicting FSI dynamics and structural responses for engineering design of pipelines, cables, wind turbines blades, airplane wings and promote the renewable energy development.
Fields of science (EuroSciVoc)
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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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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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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.
HORIZON-ERC - HORIZON ERC Grants
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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) ERC-2024-STG
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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.
4021 Stavanger
Norway
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.