European building inventory framework

Increased resilience is a strategic objective of the European strategy for disaster management, particularly concerning the protection urban areas. For the assessment of the seismic resilience of urban areas, three components are essential: a description of the hazard, an inventory of the exposed assets and an accurate estimation of their vulnerability. Exposure data have been collected during the national housing censuses and within the framework of research projects dealing with seismic risk or with the energy performance of buildings. These sources of information are reviewed with focus on the building characteristics of interest for seismic risk assessment and the space resolution. The inventories compiled within research projects contain data aggregated at the level of countries, which is not sufficient for seismic risk assessment. They were inferred from a variety of sources that present notable divergences and they do not account for the distribution of buildings in small geographical units, which is proven to influence the loss estimates. On the other hand, housing censuses cover the important building features for several countries and may be aggregated at the desired geographical areas. However, a significant effort is required to collect and elaborate the census data.JRC.G.4-European laboratory for structural assessmen

Resilience Assessment of the Built Environment of a Virtual City

L'abstract è presente nell'allegato / the abstract is in the attachmen

Assessing the transformability of public housing through bim

Public residential buildings make a large portion of the European existing stock and they quite often require deep renovation interventions. A methodology for setting priorities and targeting regeneration investments should be defined relying on the increasing use of building information modelling (BIM) tools even for managing existing buildings. The aim of this paper is to integrate the evaluation process into BIM Revit software developing a specific plug-in, a Decision support system (DSS) that will help to identify the most appropriate flats to be transformed. It is based on measuring three indicators: Usability, Fragmentation, and Constructive Modifiability. Through their weighted average it is possible to obtain a final transformability score. The proposed approach has been tested on a case study chosen within the 1st P.E.E.P. (1st public plan for council and affordable housing) that has been approved in Rome in 1964. The results demonstrate that the transformability of apartments is related mainly to the Constructive Modifiability indicator and buildings with reinforced concrete frames show higher scores. A widespread application of such a methodology on large real estate portfolio may lead stakeholders involved in housing management investments in clear choices related to maintenance of buildings

Empirical fragility curves: The effect of uncertainty in ground motion intensity

Empirical fragility curves derived from large post-disaster databases with data aggregated at municipality-level, commonly make the assumption that the ground motion intensity level is known and is determined at the centroid of each municipality from a ground motion prediction equation. A flexible Bayesian framework is applied here to the 1980 Irpinia database to explore whether more complex statistical models that account for sources of uncertainty in the intensity can significantly change the shape of the fragility curves. Through this framework the effect of explicitly modelling the uncertainty in the intensity, the spatial correlation of its intra-event component and the uncertainty due to the scatter of the buildings in the municipality are investigated. The analyses showed that the results did not change substantively with increased model complexity or the choice of prior. Nonetheless, informed decisions should be based on the defensible modelling of the significant variability in the data between municipalities

Towards disaster risk mitigation on large-scale school intervention programs

Education infrastructure is one of the main barriers on school quality in Low- and Middle-Income Countries (L&MICs), since it is insufficient and unevenly distributed. Improving the school infrastructure is needed to provide a high-quality education environment. Although research on how to improve the infrastructure is available, there is still a lack of a consistent and systematic approach to develop large-scale interventions at the national or regional level. To fill this gap, we propose a data-driven methodology with the purpose of developing a prioritization of interventions to carry out a seismic disaster risk reduction program. The method starts by identifying groups of similar buildings using clustering analysis, starting with a seismic taxonomy as descriptor (i.e., model input). Then, domain experts analyze the suggested clusters to design scalable interventions for the representative building of each cluster. The proposed data-driven methodology requires experts’ criteria in each step to validate the results and make them applicable, but significantly reduces the bias by automating the decision-making process. We use as case study the Dominican Republic public school infrastructure and present the results of the application of the proposed method. The method presented herein is extensible to other infrastructure portfolios, as well as to other types of hazards

Caesar II: An Italian decision support tool for the seismic risk. The case study of Torre Pellice, Villar Pellice and Pinerolo municipalities

Italy is a country with high seismic risk; however, a broad seismic classification of the national territory has been introduced only in the last twenty years. Therefore, most of the existing buildings stock do not comply with the current anti-seismic codes. In recent years, the seismic events that occurred in Italy have highlighted the complexity of emergency management and the great challenge for public authorities called to answer to the post-event reconstruction and the planning of effective risk prevention and mitigation measures implemented in "peacetime". In this perspective, the CAESAR II project (Controlling, Mitigating and Managing Earthquake Emergency: Cost-Benefit and Multi-criteria Analysis of Impact Scenarios for Risk Reduction and Increased Resilience) has been developed as a decision support system for public authorities engaged in the development of seismic disaster risk reduction plans. CAESAR II includes a module for the simulation of retrofitting measures applied at the municipal scale, integrating different categories of anti-seismic and energy improvement measures based on the vulnerability analysis of the existing buildings stock. The CAESAR II tool's core is the module for evaluating "seismic impact scenarios" based on the end-users' hazard. The output of the model includes information on expected damage levels for buildings (from D0-no damage to D5- total collapse) and population (dead, injured and homeless). Impact scenarios can be customised according to the minimum unit of analysis assumed (municipality or 250x250m square mesh grid) and the availability of exposure data (from national census data or survey on the spot building by building according to the PLINIVS form). Scenarios include geo-referenced data managed by geo-servers to exchange data in a format compliant with OGC (Open Gis Consortium) standards and the European INSPIRE Directive. Simulation results can be further processed through the Multi-Criteria and Cost-Benefit Analysis modules to support the comparative assessment of alternative seismic and energy measurements. In this work, the procedures included in CAESAR II are described and a case study is reported. It concerns the analysis of the expected damage assessment on buildings and population for three municipalities in northern Italy, Torre Pellice, Villar Pellice and Pinerolo (Piedmont Region)

Research needs towards a resilient community: Vulnerability reduction, infrastructural systems model, loss assessment, resilience-based design and emergency management

Most of the literature on resilience is devoted to its assessment. It seems time to move from analysis to design, to develop the tools needed to enhance resilience. Resilience enhancement, a close relative of the less fashionable risk mitigation, adds to the latter, at least in the general perception, a systemic dimension. Resilience is often paired with community, and the latter is a system. This chapter therefore discusses strategies to enhance resilience, endorses one of prevention rather than cure, and focuses in the remainder on the role played by systemic analysis, i.e. the analysis of the built environment modelled beyond a simple collection of physical assets, with due care to the associated interdependencies. Research needs are identified and include challenges in network modelling, the replacement of generic fragility curves for components, how to deal with evolving state of information

Integrated platform to assess seismic resilience at the community level

Due to the increasing frequency of disastrous events, the challenge of creating large-scale simulation models has become of major significance. Indeed, several simulation strategies and methodologies have been recently developed to explore the response of communities to natural disasters. Such models can support decision-makers during emergency operations allowing to create a global view of the emergency identifying consequences. An integrated platform that implements a community hybrid model with real-time simulation capabilities is presented in this paper. The platform's goal is to assess seismic resilience and vulnerability of critical infrastructures (e.g., built environment, power grid, socio-technical network) at the urban level, taking into account their interdependencies. Finally, different seismic scenarios have been applied to a large-scale virtual city model. The platform proved to be effective to analyze the emergency and could be used to implement countermeasures that improve community response and overall resilience