Approach
ReCharged is articulated in seven work packages, contributing to the delivery of scientific breakthroughs, transformative training and recommendations for policy.
RESEARCH & INNOVATION
ReCharged will integrate multimodal digital technologies and data to revolutionise resilience and whole-life carbon emission assessment of iTESLA based on a hybrid model/data-driven decision-making approach to combat climatic hazards.
Additionally, the project will advance and apply new management approaches and relevant regulations based on iTESLA stakeholders’ and operators’ goals and actionable metrics that incorporate e.g. cost, connectivity, resilience, whole-life carbon emissions and social factors. This will enable regulators to support capital investments through prioritization. The project will deliver system-wide consolidated assessments by quantifying iTESLA interdependencies through two robust case studies (WP2, WP3);
Efficient management
Planning, executing, and controlling of the project from start to finish to achieve project objectives, risk monitoring, and contingency planning.
Cross-Sectoral Training
The project will create a community of researchers and practitioners promoting digital literacy among engineers trained to be fit for the digital age. It will thus facilitate skill augmentation and foster cross-sectoral collaborations.
Robust Communication
ReCharged will facilitate the dissemination of new regulations to scientists, designers and the broader community. It will furthermore fuse this knowledge into the next generation of infrastructure regulations and guidelines in a participatory manner, through effective engagement with stakeholders and decision-makers.
Research Plan
Taxonomies of iTESLA ecosystems
WP2 aims to improve the resilience of critical transport and energy systems against natural hazards intensified by climate change. To achieve this, it will define taxonomies of interdependent critical transport and energy systems, identify multiple natural hazard stressors and climate projections, and document case studies to provide practical examples and insights for the development of risk management strategies. This task will focus on case studies of transport and energy systems, identifying interoperabilities and dependencies between different networks using graph theory. The delivered outcome will include documentation of data collection, topology and typology for the case studies ecosystem, and GIS databases to capturing the built assets and graph networks.
Data-driven assessment Exploiting Emerging digital Technologies
WP3 will focus is on defining the optimal digital technologies for damage identification and prediction. Digital data for the description of the iTESLA case studies will be collected, promoting use of remote sensing systems and emerging digital technologies. Advanced algorithms for data processing and interpretation, which rely on diversified monitoring information, will be developed to set up a stochastic framework for processing multi-modal data, extracting latent features, and generating labelled datasets suitable for machine learning/artificial intelligence processing. Digital data will be fused into models to derive performance indicators for iTESLA diagnosis. A hybrid method of data-driven and model-based fault diagnosis will be deployed to predict structural and operational faults and functionality loss of iTESLA by detecting damage, propagation, and cascading failures due to interdependencies.
Climate aware resilience for sustainable iTESLA
WP4 will develop novel fragility and functionality loss models, restoration and reinstatement models, data-driven resilience models, and an open visualization platform for cross-asset decision making. It focuses on the analysis of the case studies by defining engineering demand parameters for each iTESLA taxonomy and correlating asset damage to downtimes and functionality losses. Proactive adaptation and reactive restoration and reinstatement models will reflect case-study dependent conditions, streamlined according to the operators’ practices. Data-driven vulnerability and recovery models, including the assessment of physical and functionality losses, resilience, and carbon emissions, will be evaluated and fused with digital data. This work package will provide a practical lifecycle resilience and emissions framework and metrics, including the restoration strategies of iTESLA, which may lead to different carbon equivalence for different hazard and recovery scenarios.
Pilots
Three case studies have been identified and will be used as testbeds for the application of the ReCharged platform.