Statistical modelling of seismic vulnerability of RC, timber and masonry buildings from complete empirical loss data

Publisher's version (útgefin grein)In June 2000 two shallow, strike slip, Mw6.5 earthquakes occurred in the middle of the largest agricultural region in Iceland. The epicentres were close to small towns and villages and almost 5000 residential buildings were affected. A great deal of damage occurred but no residential buildings collapsed and there was no loss of life. Insurance against natural disasters is compulsory for all buildings in Iceland and they are all registered in a comprehensive official property database. Therefore, to fulfil insurance claims, a field survey was carried out after the two earthquakes where repair cost was estimated for every damaged building. By combing the loss data with the property database it was possible to establish a complete loss database, where all residential buildings in the affected area were included, both buildings with loss as well as buildings with no-loss. The main aim of the study was to fit a statistical vulnerability model to the data. Due to the high proportion of no-loss buildings in the database (~84%) a new and novel vulnerability model was used based on a zero-inflated beta regression model. The model was fitted to the three main building typologies in the affected region, i.e. low-rise structural wall RC, timber, and masonry buildings. The proposed model can be used to predict the mean and desired prediction limits of the losses for a given intensity level as well as to create fragility functions. All the typologies showed outstanding performance in the two destructive earthquakes, which is important to report, model and learn from.The authors thank the Natural Catastrophe Insurance of Iceland for placing the earthquake damage database and other relevant information at their disposal, and the University of Iceland Research Fund for financial support (Grant no. RSJ-2017 ).Peer Reviewe

Empirical vulnerability curves for Icelandic low-rise buildings based on zero-inflated beta regression model

In June 2000, two earthquakes of ~Mw6.5 struck in South Iceland, and in May 2008 the same region was hit again further west, with Mw6.3 event. Almost 5000 residential buildings were affected in each of these two seismic events. To fulfil insurance claims, detailed, and complete loss data were collected in each case, and the 2000 dataset and 2008 dataset were established. Having access to two high quality loss datasets from different size earthquakes, affecting the same building typologies in the same region, is rare to find in the literature. An advanced empirical vulnerability model based on zero-inflated beta regression was fitted to five building typologies, classified according to the GEM taxonomy system, independently for the 2000 dataset and the 2008 dataset. Status of seismic codes was considered when defining the building typologies. PGA was used as intensity measure. For all the five building typologies, the calibrated vulnerability functions and the fragility curves are substantially different from these two datasets. This indicates that PGA is not alone an adequate intensity measure to predict losses. The results also show that status of seismic code affects the performance of the buildings as one would like to see.The authors thank the Natural Catastrophe Insurance of Iceland for placing the earthquake damage database and other relevant information at their disposal. This work was partly financed by the SERICE project funded by a Grant of Excellence from the Icelandic Centre for Research (RANNIS), Grant Number: 218149-051. We also acknowledge support from the University of Iceland Research Fund

Empirical seismic vulnerability assessment of Icelandic buildings affected by the 2000 sequence of earthquakes

Publisher's version (útgefin grein)In June 2000, two Mw6.5 earthquakes occurred within a 4-day interval in the largest agricultural region of Iceland causing substantial damage and no loss of life. The distance between the earthquake epicentres and the fault rupture was approximately 15 km. Nearly 5000 low-rise residential buildings were affected, some of which were located between the faults and exposed to strong ground motion from both events. The post-earthquakes damage and repair costs for every residential building in the epicentral region were assessed for insurance purposes. The database is detailed and complete for the whole region and represents one of the best quality post-earthquake vulnerability datasets used for seismic loss estimation. Nonetheless, the construction of vulnerability curves from this database is hampered by the fact that the loss values represent the cumulative damage from two sequential earthquakes in some areas, and single earthquakes in others. A novel methodology based on beta regression is proposed here in order to define the geographical limits on areas where buildings sustained cumulative damage and predict the seismic losses for future sequence of events in each area. The results show that the average building loss in areas affected by a single event is below 10% of the building replacement value, whilst this increases to an average of 25% in areas affected by the two earthquakes. The proposed methodology can be used to empirically assess the vulnerability in other areas which experienced sequence of events such as Emilia-Romagna (Italy) in 2012.The authors wish to offer their thanks to the Icelandic Catastrophe Insurance for placing the earthquake loss database and other relevant information at their disposal, and University of Iceland for a research Grant. Ioanna Ioannou and Tiziana Rossetto’s contribution to this study was Funded by the HORIZON2020 Project ‘IMPROVER’ (Grant Number: 653390). Ioannis Kosmidis was supported by The Alan Turing Institute under the EPSRC grant EP/N510129/1 (Turing award number TU/B/000082).Peer Reviewe