Climate & Environment

    Extreme Weather Events

Joint Research Initiative

Australia

Modeling the multi-hazard vulnerability of structures to tropical cyclones

Each year, tropical cyclones cause approximately 10,000 deaths and billions of dollars of damage to buildings and infrastructure1. Since the development of natural disaster loss models in the late 20th century, engineering researchers, actuaries, and insurance or disaster risk assessment experts have sought to develop statistical models to quantify the vulnerability of structures and communities to these events. Their multi-hazard nature makes them a complex challenge, especially when it comes to structures in coastal areas, where large storm surges or river flooding can significantly increase damage.
Of the many climate hazard vulnerability models that exist for buildings, few take into account the interrelated or correlated stresses and resulting damage of tropical cyclones. As a result, estimates of damage and loss from these events are often inaccurate. In addition to this difficulty, the scope of these models is limited to residential housing in the United States, and is not applicable to other structures.

Dr. Matthew Mason of the University of Queensland, Australia, will work closely with the AXA Group's risk management team to improve the ability to model tropical cyclone vulnerability. To do this, they will develop correlation functions to couple models to a single pre-existing vulnerability factor (e.g., wind or flooding) to accurately estimate tropical cyclone losses to commercial and industrial infrastructure worldwide. These correlations will be developed for various building typologies that are located in cyclone-prone regions of the world, using an approach that combines empirical analysis of loss data with theoretical structural engineering calculations.

Published on 05/27/2021

Matthew
MASON

Institution

The University of Queensland

Country

Australia

Nationality

Australian

ORCID Open Researcher and Contributor ID, a unique and persistent identifier to researchers

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