Seismic risk management of insurance losses using extreme value theory and copula - Seismic Risk Analysis and Management of Civil Infrastructure Systems - page 763

Δ ij ,
T i , T j ) in Equation [28.11c]) are adopted in this study: the GH08 model
(Goda and Hong, 2008) for shallow crustal earthquakes in North America,
and the GA09 model (Goda and Atkinson, 2009, 2010) for Japanese earth-
quakes. The GH08 model may be suitable for shallow crustal earthquakes
in western Canada, as it is based on statistical analysis of strong ground
motion records from the PEER-NGA database (http://peer.berkeley.edu/
nga/index.html), while the GA09 model may be applicable to in-slab and
interface earthquakes in the Cascadia subduction zone, because many
GMPEs for subduction earthquakes have been developed by including
ground motion records from the K-NET and KiK-net databases (http://
www.kyoshin.bosai.go.jp/). The details of the correlation models can be
found in Goda and Hong (2008) and Goda and Atkinson (2009, 2010).
Generally, the GA09 model predicts higher correlation than the GH08
model for the same separation distance, and the decay of the correlation
coeffi cient as a function of separation distance is more gradual for the
GA09 model than the GH08 model.
The above-mentioned analysis is carried out based on Monte Carlo simu-
lation (see Chapter 1). Initially, earthquake occurrence models, seismic
source zones, and magnitude-recurrence relations are used to produce a
synthetic earthquake catalogue (see Panel 1 in Fig. 28.1). Then, by using
suitable ground motion models and spatial correlation models of peak
ground motions and response spectra, simultaneous seismic effects at dif-
ferent locations are generated for each seismic event (see Panel 2 in Fig.
28.1). These two steps generate probabilistic estimates of elastic seismic
demands at multiple sites for many seismic events over a certain period (i.e.
multiple seismic intensity maps). This information is used as input in seismic
vulnerability analysis.

Two spatial correlation models of seismic effects (i.e. ρ η ( T i , T j ) and ρ ε (

28.3.2 Seismic vulnerability and loss assessment of
wood-frame houses

Structural vulnerability models quantify the extent of structural damage for
a given seismic excitation, and have signifi cant impact on seismic loss esti-
mation. The fi rst task is to collect comprehensive building inventory infor-
mation, such as location, structural and material type, age, story number,
occupancy type, fl oor area, value, and local soil condition (Panel 3 in Fig.
28.1). The building inventory database is the key input in seismic loss esti-
mation, and determines overall accuracy of the assessment. Based on the
collected building information, a suitable structural model and analysis
method need to be selected by achieving a reasonable balance between
accuracy and computational effi ciency. Damage severity assessment is then
carried out by directly comparing sustained inelastic seismic demand with