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The use of digital representations of physical objects allows to simulate phenomena and predict behaviours. The representativeness of a model is based on the congruency between the code, the survey and the modelling strategies. In terms of physical space, two important approaches are the Geographical Information Systems (GIS) and Building Information Modelling (BIM). GIS approach is intended to code environmental information based on geographical references. BIM approach is intended to code buildings in terms of their components, generating parametric descriptions. For historic buildings, BIM extends to the so-called Historical BIM models (HBIM). Together, these strategies allow coding territorial-scale entities, such as historical centres. An application for these models would be the simulation of risk situations, leading to vulnerability analysis. Despite the existence of GIS-BIM-HBIM integration examples, most of their procedures are designed to fit with a specific case study, which questions the suitability of a general coding framework. This paper presents a vision of state-of-the-art technologies and strategies for coding, surveying and model historical centres, with emphases on the analysis of urban vulnerability and risk. Finally, we propose a general comprehensive framework on the convergences of GIS-BIM-HBIM technologies and successful practices. [ABSTRACT FROM AUTHOR]

On 12th November 2017, an earthquake with a magnitude of 7.3 Richter scale in the town of Sarpol-e Zahab took place that caused lots of human casualties and devastation. After the incident, issues related to the probability of an earthquake with equal intensity and extents of similar building destruction were raised in Kermanshah city. Therefore, a seismic microzonation map of Kermanshah city has been prepared based on the geotechnical, geological, and geophysical data, and the data were analysed using Fuzzy analytic hierarchy process (AHP). In the next step, the vulnerability analysis of city buildings was carried out based on the ground-shaking map, vulnerability curves, and statistical data regarding the buildings. The results of the vulnerability rate of residential buildings indicate that 80% of residential buildings would be exposed to vulnerability from low to moderate. However, other buildings would suffer 2% fully destruction (D1), 7% very high destruction (D2) and 11% high destruction (D3), respectively. Finally, according to the obtained results, the proposed model is verified with the help of the data and observations from the Sarpol-e Zahab earthquake, which reveals that the model is in good agreement with the actual earthquake data. [ABSTRACT FROM AUTHOR]

The vulnerability index and capacity spectrum-based methods used to assess the expected physical damage in dwellings are revisited, and their main advantages and shortcomings are analyzed and discussed. Then, a vulnerability index-based method is used to assess the expected damage in the oldest district of Barcelona, Spain. The risk analysis is performed for earthquake scenarios defined by macroseismic intensities of V, V-VI, VI, VI-VII, and VII to design seismic emergency plans. According to the Spanish Seismic Code, the basic peak ground acceleration for a 475-year return period is 0.04 g, which corresponds to an intensity of VI. Thus, the expected physical damage is quantified and its impact on population and other quantities, such as debris and economic cost, are studied. In spite of the low-to-moderate seismic hazard in Barcelona, the results show that the risk is high, due to the high exposure and vulnerability of the built environment. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop regional vulnerability functions of buildings to estimate the loss from windstorms. Windstorms trigger critical financial damage to assets around the world. Insurance companies assess the financial risk of their exposures by employing windstorm risk assessment models. The vulnerability function in the risk assessment model is generally based on the analysis of actual damage records from insurance companies. However, the absence of detailed loss data is an obstacle to developing vulnerability functions. To fill this gap, this study provides a methodology to develop a function using an insurance company's loss data associated with windstorms. Vulnerability functions are generated based on the wind speed, line of business, and value of the property. The findings and methodology of this study offer a practical way of reflecting the real economic losses and regional vulnerability of buildings and help to develop vulnerability functions for insurance companies and emergency planners. [ABSTRACT FROM AUTHOR]