Active Engineering Clean Energy

ReCharged - Climate-aware Resilience for Sustainable Critical and interdependent Infrastructure Systems enhanced by emerging Digital Technologies.

In plain English

AI plain-English summary

A new digital platform will help engineers and planners decide, within minutes rather than hours, how to repair roads and power lines after a storm while also cutting carbon emissions. This matters because transport and energy systems are deeply interdependent—a flooded road can block access to a substation, and a power cut can shut down a railway signal. Currently, infrastructure managers assess climate resilience and carbon emissions separately, using different methods that cannot be easily combined. The ReCharged project will create a single visualisation platform that accounts for these interdependencies and tracks whole-life carbon emissions alongside recovery times. If successful, the platform could accelerate post-hazard recovery and reduce carbon emissions by 50% in the two case studies tested. Faster decision-making—up to 50% quicker—would mean less disruption to daily life after extreme weather events. The project also aims to break down siloed thinking between transport and energy authorities, creating a community of practitioners who share data and methods. New jobs and training opportunities are expected as the digital tools are adopted across Europe.

View original technical description
ReCharged is a transformative project that has the vision to develop a new integrated framework toward a practical visualisation platform in order to optimise and streamline climate resilience and whole-life carbon emission assessments for interdependent Transport and Energy Systems, Lifelines and Assets (iTESLA). To achieve this, ReCharged harnesses the power of digital technologies and data to quantify the functionality and recovery of iTESLA after hazards. This is in response to the lack of methods of assessment and communicable visualisations of consolidated climate resilience and whole-life carbon emission metrics for iTESLA. ReCharged will account for interdependencies that lead to failure propagation in transport and energy systems, to accelerate post-hazard recovery, mitigate losses and societal ramifications due to climate change. In doing so, ReCharged underpins synergies and participatory decision-making to combat siloed thinking in infrastructure management. This project will lead to 50% faster decision-making in iTESLA management, 50% reduction of carbon emissions for the two case studies analysed, create new jobs, and make Europeans fit for the Digital Age. ReCharged is a synergy that combines the exchange of interdisciplinary knowledge and tailored training of staff, through an alliance between leading academic institutions, industrial partners, SMEs, and a research and technology center. All beneficiaries are committed to exploiting and transferring their skills and knowledge, to incentivise data-driven resilience toward climate adaptation and reduce emissions in critical infrastructure. ReCharged will augment researchers' skills and career perspectives, create a community of practitioners, improve critical infrastructure, and ultimately make people feel safer.

View the original record at the funder ↗

Researchers

Stergios Mitoulis (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Climate-aware Resilience for Sustainable Critical and interdependent Infrastructure Systems enhanced by emerging Digital Technologies
ReCharged - Climate-aware Resilience for Sustainable Critical and interdependent Infrastructure Systems enhanced by emerging Digital Technologies
Recharged Climate aware resilience for sustainable critical and interdependent infrastructure systems enhanced by emerging digital technologies
Resilient Critical Infrastructures in Energy Transformation
Open KE Fellowship - MEDIATE: Overcoming barriers to MaximisE Data potential for better blue-green-grey InfrAsTructurE

Original classification

Research Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.