Mini symposia/Special sessions

MS58 Implementation of Artificial Intelligence and Digital Technologies in Disaster Risk Assessment and Simulation of Civil Infrastructure under Extreme Events

Prof. Fulvio Parisi:

Session Chairs:
Dr. Emanuele Brunesi , EUCENTRE, Pavia, Italy,
Prof. Xinzheng Lu , Tsinghua University, Beijing, China,
Prof. Fulvio Parisi , University of Naples Federico II, Naples, Italy,

Abstract of the special session:
The performance-based engineering (PBE) framework for structural design and assessment has been gradually incorporated in building codes at both national and international levels. Probabilistic methodologies for quantitative risk analysis of civil infrastructure have been originally formulated and implemented in the field of earthquake engineering, with only a few pioneering studies on structural safety and loss assessment of constructions subjected to extreme hazards or, equivalently, low-probability/high-consequence (LPHC) events. Nonetheless, the progressive increase in frequency and/or intensity of LPHC events due to climate change, terrorism/war scenarios, and other natural, socio-political, and economic phenomena, call for probability-based methods that allow a rational and transparent approach to disaster risk assessment and mitigation. In this respect, the ever-increasing availability, use, and interconnection of digital technologies, together with artificial intelligence (AI) algorithms, can significantly expand and foster the application of probabilistic studies in civil engineering.
This Mini-Symposium aims at collecting and discussing research studies on civil infrastructure subjected to extreme events, with special emphasis on the incorporation of data-driven methods in PBE methodologies, disaster risk assessment, and simulation. Contributions on the following topics are welcome:

  • Probabilistic modelling of extreme hazards (e.g., in terms of characterization of frequency and intensity of single events, triggering of cascade events, and simulation of their spatio-temporal evolution).
  • Probabilistic analysis of structural response, progressive collapse resistance and robustness to extreme loading conditions related to natural events (e.g., hurricanes, landslides, floods, megathrust earthquakes), human-related events (e.g., impact, fire, explosions, human errors in design, construction, usage or maintenance) and cascade events (e.g., earthquake-induced landslides, fires or explosions).
  • Vulnerability assessment of structures and infrastructure systems, also including their interaction with the natural environment (e.g., soil-structure or fluid-structure interaction) and deterioration phenomena (e.g., steel corrosion and concrete degradation).
  • Quantitative assessment of social and/or economic consequences of extreme hazards at multiple territorial scales (e.g., site-specific, multi-site, regional), including multi-hazard risk assessment methods.
  • Digital technologies supporting computational simulations at single or multiple spatial scales (e.g., drones, smart monitoring networks, cloud computing systems, virtual/augmented/mixed reality devices, satellites).
  • Computational strategies, AI algorithms, and software development for probabilistic risk assessment, disaster simulation, post-disaster damage assessment.

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