Summary
Adapting to the increasing threat of natural hazards is one of the most pressing current societal issues. Specifically, seismic risk reduction and adaptation of complex intertwined industrial facilities are keys for an effective EU green transition. Nevertheless, the most common policies still rely only on static risk analyses, neglecting temporal and spatial interactions.
In fact, no one has yet tackled the critical aspect of industrial system adaptation, accounting for the dynamics of the hazard, of the system itself and its recovery processes. This comes with no surprises, as system adaptation is a highly complex stochastic process, deeply rooted into the future, where uncertainties at all levels play a crucial role.
This critical research gap is filled with the “Seismic Risk Reduction and Adaptation for Complex Time-dependent Industrial Systems” (REACTIS) project, which is the first integrated uncertainty quantification (UQ)-based methodology that aims to solve these open questions.
The project will examine the stochastic dynamics of the performance of industrial facilities subjected to time-variant seismic hazards. In particular, the recovery processes of the systems will be deepened and treated from a UQ and stochastic dynamics perspective.
Building upon preliminary collaboration, the project will focus on the stochastic dynamics and recovery of a single 1-node system. Then, a real-world complex industrial case study will be deployed. Leveraging concepts from spatial statistics and graph theory, the intertwined network topology of the industrial system will be mapped. Specifically, the evolution of the dynamics of the system will be extended to a m-nodes, initially deterministic, then random, network configuration. Finally, our research will encompass an in-depth analysis of seismic risk and adaptation strategies formulation. This effort aims to identify the criticalities and vulnerabilities within the industrial system networks.
In fact, no one has yet tackled the critical aspect of industrial system adaptation, accounting for the dynamics of the hazard, of the system itself and its recovery processes. This comes with no surprises, as system adaptation is a highly complex stochastic process, deeply rooted into the future, where uncertainties at all levels play a crucial role.
This critical research gap is filled with the “Seismic Risk Reduction and Adaptation for Complex Time-dependent Industrial Systems” (REACTIS) project, which is the first integrated uncertainty quantification (UQ)-based methodology that aims to solve these open questions.
The project will examine the stochastic dynamics of the performance of industrial facilities subjected to time-variant seismic hazards. In particular, the recovery processes of the systems will be deepened and treated from a UQ and stochastic dynamics perspective.
Building upon preliminary collaboration, the project will focus on the stochastic dynamics and recovery of a single 1-node system. Then, a real-world complex industrial case study will be deployed. Leveraging concepts from spatial statistics and graph theory, the intertwined network topology of the industrial system will be mapped. Specifically, the evolution of the dynamics of the system will be extended to a m-nodes, initially deterministic, then random, network configuration. Finally, our research will encompass an in-depth analysis of seismic risk and adaptation strategies formulation. This effort aims to identify the criticalities and vulnerabilities within the industrial system networks.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101147351 |
| Start date: | 01-10-2024 |
| End date: | 30-09-2027 |
| Total budget - Public funding: | - 297 164,00 Euro |
Cordis data
Original description
Adapting to the increasing threat of natural hazards is one of the most pressing current societal issues. Specifically, seismic risk reduction and adaptation of complex intertwined industrial facilities are keys for an effective EU green transition. Nevertheless, the most common policies still rely only on static risk analyses, neglecting temporal and spatial interactions.In fact, no one has yet tackled the critical aspect of industrial system adaptation, accounting for the dynamics of the hazard, of the system itself and its recovery processes. This comes with no surprises, as system adaptation is a highly complex stochastic process, deeply rooted into the future, where uncertainties at all levels play a crucial role.
This critical research gap is filled with the “Seismic Risk Reduction and Adaptation for Complex Time-dependent Industrial Systems” (REACTIS) project, which is the first integrated uncertainty quantification (UQ)-based methodology that aims to solve these open questions.
The project will examine the stochastic dynamics of the performance of industrial facilities subjected to time-variant seismic hazards. In particular, the recovery processes of the systems will be deepened and treated from a UQ and stochastic dynamics perspective.
Building upon preliminary collaboration, the project will focus on the stochastic dynamics and recovery of a single 1-node system. Then, a real-world complex industrial case study will be deployed. Leveraging concepts from spatial statistics and graph theory, the intertwined network topology of the industrial system will be mapped. Specifically, the evolution of the dynamics of the system will be extended to a m-nodes, initially deterministic, then random, network configuration. Finally, our research will encompass an in-depth analysis of seismic risk and adaptation strategies formulation. This effort aims to identify the criticalities and vulnerabilities within the industrial system networks.
Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
22-11-2024
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