Team Name
Climate change and challenges to nuclear plant safety – AI/ML analysis of extreme weather events
Track
Energy
Use Case
An analysis of long-term worldwide extreme event records using AI and machine learning techniques will reveal valuable insights for nuclear safety. The study may identify trends in various natural hazards (hydrological, meteorological, drought, wildfire, etc.), uncover correlations between hazards of different types, analyze hazard characteristics and affected world regions, and estimate probability of occurrence and induced risk to nuclear installations. The outcome may well support a better understanding of the natural hazard scenarios, ultimately contributing to more effective safety assessments for nuclear installations
Technology
AI/ML
Region
EMEA
Team lead
Paolo Contri
Team members
(1) Name: Paolo Contri (Team Leader)
Organization: IAEA (International Atomic Energy Agency)
Email: P.Contri@iaea.org
(2) Name: Jan Stowisek
Organization: IAEA (International Atomic Energy Agency)
Email: J.Stowisek@iaea.org
(3) Name: Vijayan Sugumaran (Professor)
Organization: Oakland University
Email: sugumara@oakland.edu
(4) Name - Aswini Sivakumar (Graduate Student)
Organization: Oakland University
Email - aswinisivakumar@oakland.edu
(5) Name - Yashashri Kadam (Graduate Student)
Email - yashashriarvind@oakland.edu
Organization: Oakland University
(6) Name: Chris Chiesa
Organization: PDC (Pacific Disaster Center)
Email: cchiesa@pdc.org
(7) Name: Cassie Stelow
Organization: PDC (Pacific Disaster Center)
Email: cstelow@pdc.org
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