Such models incorporate detailed databases and scientific understanding of the highly complex physical phenomena of natural hazards, and engineering expertise about how infrastructure, buildings and their contents respond to those hazards.

Our research in this area focuses on the development and use of advanced probabilistic and statistical methods for modelling and managing risk caused by extreme loads on the built environment, with an emphasis on earthquakes and wind hazards. We are collaborating with national and international research institutions and stakeholders to promote CAT risk engineering (CRE).

Recent advances in this area by our group include:

  • the generation, validation and use of physics-based and stochastic simulated ground motions for seismic risk modelling (in collaboration with the Southern California Earthquake Centre (SCEC), the University of California, Irvine, and the University of Notre Dame)
  • the development of a real-time, Bayesian, CAT modelling framework for designing engineering applications of earthquake early warning in Italy and Mexico
  • the development of a framework for multi-hazard risk assessment and risk-based design of offshore wind energy technology in Europe (in collaboration with AIR Worldwide)
  • the development of innovative statistical algorithms for modelling ground motion spatial correlations and uncertainties for seismic loss estimation (a collaboration with UCL’s Department of Statistical Science and CEA, the China Earthquake Administration)
  • the development of a framework for modelling wind-induced fatigue followed by seismic fracture in high-rise steel-moment frames in California (in collaboration with the University of California, Davis, and the Willis Research Network).

Authors

Carmine Galasso, Chen Huang, Biao Song, Alexandra Tsioulou, Omar Velazquez (UCL Earth Sciences), David Wilkie