|Reference:||Oxford Research Encyclopedia of Natural Hazard Science|
|ISBN / DOI:||DOI: 10.1093/acrefore/9780199389407.013.71.|
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Natural Hazard Science. Please check back later for the full article.
In the fields of earthquake engineering and seismic risk reduction, the term physical vulnerability defines the component that translates the relationship between seismic shaking intensity, dynamic structural response (physical damage), and cost of repair for a particular class of buildings or infrastructure facilities. The concept of physical vulnerability was started in the early 1980s, with the development of the earthquake damage and loss assessment discipline, which aimed at predicting the consequences of earthquake shaking to an individual building or a portfolio of buildings. Nowadays, physical vulnerability has become one of the key components used by agencies as model input data when developing prevention and mitigation actions, code provisions, and guidelines. The same may apply to the insurance and re-insurance industry in developing catastrophe models (also known as CAT models).
Over the past years, a blossoming of methodologies and procedures could be observed, ranging from empirical to basic and more advanced analytical, implemented for modeling and measuring physical vulnerability. These methods use approaches that differ in terms of level of complexity, calculation efforts (in evaluating the seismic demand-to-structural response and damage analysis), and modeling assumptions adopted in the development process. At this stage, one of the challenges often encountered is that some of these assumptions may highly affect the reliability and accuracy of the resultant physical vulnerability models in a negative way, hence introducing important uncertainties in estimating and predicting the inherent risk (i.e., estimated damage and losses).
Other challenges that are commonly encountered when developing physical vulnerability models are the non-availability of exposure information and the lack of knowledge due to technical or nontechnical problems, like, such as inventory data that would allow for an accurate building stock modeling, or economic data that would allow for a better conversion from damage to monetary losses. Hence, these physical vulnerability models carry different types of intrinsic uncertainties of both aleatory and epistemic character. To come up with appropriate predictions on expected damage and losses of an individual asset (e.g., a building) or a class of assets (e.g., a building typology class, a group of buildings), reliable physical vulnerability models have to be generated that consider all these peculiarities and the associated intrinsic uncertainties at each stage of the development process.