See more on the CORDIS website https://cordis.europa.eu/project/id/101093939
and in RISKADAPT website: http://riskadapt.eu/
RISKADAPT is a € 2.5 million project funded by Horizon Europe HORIZON-MISS-2021-CLIMA-02.
A multidisciplinary and multipartner project with 18 partners.
Title: RISKADAPT- Asset-level modelling of risks in the face of climate-induced extreme events and adaptation
Metainfrastructure will be leading WP6 which is the case studies of the project.
A few words about the project:
RISKADAPT will provide, in close cooperation with the end-users & stakeholders, a novel, integrated, modular, interoperable, public and free, customizable user-friendly platform, to support systemic, risk-informed decisions regarding adaptation to climate change induced compound events at the asset level, focusing on the structural system. RISKADAPT will explicitly model dependencies between infrastructures, which, inter alia, will provide a better understanding of the nexus between climate hazards and social vulnerabilities and resilience. Moreover, this project will identify gaps in data and propose ways to overcome them and advance the state of the art of asset-level modelling through advanced climate science to predict climate change forcing on the structure of interest, structural analyses, customized to the specific structure of interest, that consider all major climate change induced load effects in tandem with material deterioration, novel probabilistic environmental life cycle assessment (LCA) and life cycle cost (LCC) of structural adaptation measures and a new model to assess climate risk that will combine technical risk assessment with an assessment of social risks.
This is of particular interest to the infrastructuResilience group as the landmark Polyfytos Bridge shown below will be one of the main case studies of this project and we will try to identify optimised adaptation strategies leading to minimum social impacts for the local community.
Leader: RISA Germany
The project is in support of climate change, structural adaptation in a sustainable manner, and resilience using digital data – digitalisation
Related publications:
- Izonin, I., Nesterenko, I., Kazantzi, A.K. et al. Enhanced ANN-based ensemble method for bridge damage characterization using limited dataset. Sci Rep 14, 24395 (2024). https://doi.org/10.1038/s41598-024-73738-5
- Izonin I, Kazantzi A, Tkachenko R, Mitoulis SA (2024). GRNN-based Cascade Ensemble Model for Non-Destructive Damage State Identification: Small Data Approach. Engineering with Computers. https://doi.org/10.1007/s00366-024-02048-1
- Kazantzi, A. K., Moutsianos, S., Bakalis, K., Mitoulis, S. A. (2024). Cause-agnostic bridge damage state identification utilising machine learning. Engineering Structures, 320, 118887. https://doi.org/10.1016/j.engstruct.2024.118887