Project description
More resilient infrastructure with smart non-linear vibration control
Europe’s infrastructure including roads, bridges and offshore energy structures faces growing threats from vibrational forces associated with earthquakes, wind, waves and traffic. Conventional vibration control systems often fail under complex, highly non-linear, real-world conditions. With the support of the Marie Skłodowska-Curie Actions programme, the SMART-M project aims to develop a next-generation adaptive damping system combining magnetorheological elastomers (materials whose mechanical properties change in a magnetic field) with high-damping rubber bearings and intelligent deep learning control algorithms. This hybrid system will enable real-time vibration mitigation and structural health monitoring. Validated through accelerated aging tests and life-cycle assessment, the system could enable safer, more durable and cost-effective infrastructure resilient to multiple climate and seismic hazards.
Objective
The global demand for resilient vibration control technologies in civil, bridge, and offshore infrastructure is rapidly increasing due to complex multi-hazard environments. Conventional damping systems often fail under highly nonlinear excitations, as demonstrated by historical infrastructure failures such as the Morandi Viaduct bridge collapse and offshore wind turbine damage. The SMART-M project addresses this urgent need by developing a next-generation magneto-adaptive resilient technology that integrates magnetorheological elastomers (MRE) with high-damping rubber bearings (HDRB), enhanced by intelligent, data-driven control algorithms. This combination enables real-time adaptive vibration mitigation, structural health monitoring, and long-term resilience against wind, seismic, traffic, and wave-induced excitations.
The project will design and optimize the hybrid system using nonlinear finite element simulations with reduced-order models for MRE-based damping systems, enabling efficient, accurate predictions and robust optimization validated against experiments. Deep reinforcement learning (DRL) and physics-informed neural networks (PINN) will be employed to deliver for real-time vibration control and condition monitoring of advanced nonlinear vibration control in complex structure. A multi-mode damping architecture will allow seamless transitions between passive, semi-active, and active control, ensuring energy-efficient performance. Long-term durability and sustainability will be validated through accelerated aging tests and a life-cycle assessment.
SMART-M will set a new benchmark in learning-enabled vibration control, supporting EU seismic risk policies and the Mission “Climate Adaptation”, while ensuring safer, sustainable structures and reducing maintenance costs. It delivers a transformative solution aligned with the MSCA Green Charter and Horizon Europe mission-driven innovation goals for climate-resilient, digitally enabled, and safe built environments.
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 ecosystem-based management climate change adaptation
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- engineering and technology environmental engineering energy and fuels renewable energy wind energy
- social sciences sociology governance crisis management seismic risk management
- natural sciences computer and information sciences artificial intelligence computational intelligence
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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.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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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-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2025-PF
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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.
60121 Ancona
Italy
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.