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This paper focuses on seismic fragility and damage scenario assessment of minor Italian historical centres through the development of urban fragility curves. With reference to the case study of Balvano, a small centre located in Basilicata Region of Italy, two hybrid models have been adopted. The first is a mechanic-based hybrid model developed by the authors to derive urban fragility curves specifically; the second is the macroseismic method, originally conceived to derive typological fragility curves for single building classes, expanded to derive urban fragility curve herein. Balvano was strongly struck by 1980 Irpinia-Basilicata earthquake (Ms = 6.90) and hence subjected to an intense reconstruction process during 1980s, where almost the 80% of the buildings were reconstructed with reinforced concrete structures in the place of unreinforced masonry ones. Seismic vulnerability and damage scenarios before and after 1980 have been assessed and compared with the purpose of validating the effectiveness of the urban scale fragility curves obtained through hybrid methodologies and quantifying the effect of the 'new' seismic hazard maps and first seismic codes and recommendations released by the Italian Government in the aftermath of 1980 for the construction of new buildings or for retrofitting the existing ones. A good matching between predicted and occurred damage scenario from the research outcomes emerged, confirming the effectiveness of the urban scale hybrid fragility curves to assess seismic vulnerability at urban scale. Moreover, the comparison of the damage scenarios pre and post-reconstruction highlighted the crucial role played by the code prescriptions adopted in that years for reducing the seismic vulnerability of the municipality and the importance of the 'new' seismic hazard maps introduced in 1980s. Finally, the differences between mechanical-based hybrid and macroseismic model have been discussed in the paper. [ABSTRACT FROM AUTHOR]

The Department of Civil Protection (DPC), in compliance with the EU decision 1313/2013 and at the request of the Sendai Framework for Disaster Risk Reduction 2015–2030 to update the disaster risk assessments by various countries, released the latest National Risk Assessment for Italy at the end of 2018. Specifically, as regards the seismic risk assessment, six research units belonging to two centres of competence of the DPC collaborated under its guidance to update the risk maps of the Italian residential heritage. This extensive collaboration complied with the recent Italian code for Civil Protection, which requires a broad scientific consensus for risk assessment. During this research activity, six fragility models were developed, according to some common criteria (four for masonry buildings and two for RC buildings). These models were then implemented by the DPC for the definition of the national seismic risk. Within this context, the aim of this paper is to evaluate the risk results provided by these models, compare their features, and assess and validate their prediction capabilities. In particular, this paper shows the comparison of predicted and observed damage scenarios and consequences on building stock and the population of two seismic events, i.e. L'Aquila 2009 and Amatrice 2016. Furthermore, the paper provides some interesting damage and risk predictions at a national level. Overall, the forecasts and comparisons made in this study demonstrate the validity of the approach adopted by the DPC for the assessment of national seismic risk. [ABSTRACT FROM AUTHOR]

This paper illustrates the derivation of an empirical fragility model for residential unreinforced masonry (URM) buildings, calibrated on Italian post-earthquake damage data and compatible with the key features of the Italian national seismic risk platform. Seismic vulnerability is described by fragility functions for three vulnerability classes, then refined based on the building height. To this aim, a clustering strategy is implemented to merge predefined building typologies into vulnerability classes, based on the similarity of the observed seismic fragility. On the other side, a specific procedure is built up to determine the vulnerability composition of the exposed URM building stock, starting from national census data. The empirically-derived model was implemented into the national seismic risk platform and used, together with other vulnerability models, for assessing seismic risk in Italy. The results presented in this paper, consisting of refined typological fragility curves and fragility curves for vulnerability classes, can be also exploited for estimating both expected seismic damage and risk in sites with similar seismic hazard and building inventory. [ABSTRACT FROM AUTHOR]

In May 2012, two strong earthquakes hit the northern Italy revealing the significant seismic vulnerability of precast reinforced concrete structures and causing severe damage and many collapses, and high economic losses. After the lesson learnt from these events, more reliable seismic design criteria have been established for the design of new structures and different approaches have been proposed for the seismic assessment of the existing structures. In this context, the paper presents the results of a first application of the PRESSAFE-disp method, recently proposed by the authors, allowing to define the fragility curves of precast RC buildings at various limit states, including collapse. A stock of 91 precast buildings in the industrial area of San Felice sul Panaro (Modena) was selected as a benchmark case study to verify the reliability of the method in assessing seismic damage scenarios. In particular, with reference to the 2012 seismic ground-motion, two large-scale stochastic models are outlined to predict the number of the buildings collapsed in the area. The first one is based on a Monte Carlo simulation which incorporates the evaluation of the uncertainties, while the second one is a direct simplified calculation. Comparative considerations on the outcomes of the two methods for different seismic intensities are discussed, including the directionality effect of the ground-motion. To test the soundness of the simulations, the results of the two methods are compared with the real data collected through in-situ surveys. The procedures proposed here result, on average, in good agreement with the observed damage scenario. It is worth noting that, due to the inherent simplicity of the methods, they could be implemented to perform scenario-based seismic loss assessments to estimate the financial consequences of an earthquake affecting one or more industrial areas, and to drive the decision-making process for the seismic retrofit of existing precast RC buildings. [ABSTRACT FROM AUTHOR]

Post-earthquake reconstruction activities need tools for assessing the vulnerability of structures, based on visual inspection and quick survey. So far, the public administrations in charge of granting the funds and monitoring reconstruction have adopted different methods taken from scientific literature or developed ad hoc for specific events. The time is ripe for a standard method to be developed, treasuring from the lessons learned in the field. This paper proposes an expeditious tool based on visual survey for the assessment of the seismic vulnerability of unreinforced masonry buildings, starting from available methods, whose parameters were reassessed and recalibrated, and scientific evidence from recent literature. The influence of the main structural features was considered to calculate a vulnerability index in the 0–100 range. The effects of materials and arrangement of masonry were quantitatively evaluated through the masonry quality index, which represents an advancement with respect to current practice. The method was validated on a sample of 50 masonry aggregates and nearly 200 structural units of L'Aquila, Italy, where reconstruction is underway after a destructive earthquake in 2009. The sample is representative of the built heritage of other earthquake prone areas in Italy and many European Countries and the proposed method is a step forward the development of a standard tool to be used in future post-earthquake reconstruction scenarios. [ABSTRACT FROM AUTHOR]

The paper presents a mechanical-based framework for the evaluation of local-scale seismic fragility curves. The approach is oriented to a seismic vulnerability assessment of unreinforced masonry buildings and makes use of basic exposure data easily obtained from survey or available in existing database. An efficient finite element model and static nonlinear analyses are employed to assess the structural behaviour. The mechanical-based fragility curves are evaluated using Monte Carlo simulations that allow to account for the uncertainties propagation. The proposed approach is tested on a case-study regarding the city centre of Cosenza, in southern Italy, using exposure information available from CARTIS database. [ABSTRACT FROM AUTHOR]

In this paper, empirical fragility curves for reinforced concrete buildings are derived, based on post-earthquake damage data collected in the aftermath of earthquakes occurred in Italy in the period 1976–2012. These data, made available through an online platform called Da.D.O., provide information on building position, building characteristics and damage detected on different structural components. A critical review of this huge amount of data is carried out to guarantee the consistency among all the considered databases. Then, an in-depth analysis of the degree of completeness of the survey campaign is made, aiming at the identification of the Municipalities subjected to a partial survey campaign, which are discarded from fragility analysis. At the end of this stage, only the Irpinia 1980 and L'Aquila 2009 databases are considered for further elaborations, as fully complying with these criteria. The resulting database is then integrated with non-inspected buildings sited in less affected areas (assumed undamaged), to account for the negative evidence of damage. The PGA evaluated from the shakemaps of the Italian National Institute of Geophysics and Volcanology (INGV) and a metric based on six damage levels according to EMS-98 are used for fragility analysis. The damage levels are obtained from observed damage collected during post-earthquake inspections through existing conversion rules, considering damage to vertical structures and infills/partitions. The maximum damage level observed on vertical structures and infills/partitions is then associated to the whole building. Fragility curves for two vulnerability classes, C2 and D, further subdivided into three classes of building height, are obtained from those derived for specific structural typologies (identified based on building height and type of design), using their frequency of occurrence at national level as weights. [ABSTRACT FROM AUTHOR]

Following a seismic event that occurred years ago in Central Italy, the public opinion was growing and growing a concern on the adequacy of educational buildings all across Italy. This activated several political decisions and a consequent technical effort is in progress. Technically speaking one has to manage the classical problem of retrofitting existing buildings. However, the legal environment goes across national codes, targeted guidelines and the professional need of achieving pragmatic solutions based on ethical and social acceptation schemes.This paper introduces the topic in its worldwide exception and focuses then on some operative aspects in the Italian situation. It outlines the consolidated steps along this technical process and emphasizes the weak aspects one meets when going across the designers' reports. [ABSTRACT FROM AUTHOR]

The paper presents a detailed report on a large sample of masonry churches damaged by the 2016–2017 Central Italy seismic sequence. The first part of the work analyses the seismic sequence to give an overview of the occurred events in terms of both ground motion parameters and macro-seismic intensities. The surveyed data are organized into a database made, to date, of 990 cases, which represent almost one-fourth of the whole surveys performed during the emergency phase. Such a significant statistical sample was used to carry out a regional scale typological analysis in order to identify the most recurrent typologies of churches present in Central Italy. The analysis of the observed damage and usability outcomes allowed drawing some conclusions on the behaviour of the inspected churches under the 2016–2017 seismic sequence. The collected data were used to create damage probability matrixes for homogeneous classes of churches at different damage levels and, successively, to implement the corresponding fragility curves in terms of PGA. [ABSTRACT FROM AUTHOR]

This paper addresses the large-scale classification of the seismic vulnerability of nonstructural components in school buildings. A rapid visual screening methodology is proposed that highlights the factors that likely have a major effect on the seismic behavior of nonstructural building components. This methodology is based primarily on questionnaire forms that are used to construct a nonstructural index and priority ranking that identifies the most vulnerable category of nonstructural components. Because numerical answers in the questionnaires can produce unreliable results, a calibration of the categories by weight is proposed via fragility functions to obtain a vulnerability index. Finally, the developed methodology is applied to a case study of school buildings in Italy. [ABSTRACT FROM AUTHOR]

Soon after the earthquake that damaged L'Aquila municipality and its Province in the Abruzzi Region, Italy, on the 6th of April 2009, a widespread damage and usability assessment of buildings was launched. In 3 months, about 70,000 buildings were inspected, with the AeDES form, by public servants and professionals coordinated by the Italian Civil Protection Department. The paper, after describing the procedures and the form that were used for the assessment, discusses the time evolution of the inspections and analyses the data on building type and seismic damage. The empirical damage distribution conditional upon seismic intensity and building type is provided and the role of several vulnerability factors, such as the quality of masonry, the construction year, the number of stories, and the pre-existing damage, is highlighted. Lastly the damage consequences, such as the immediate occupancy conditional upon building damage and building type, are reported. [ABSTRACT FROM AUTHOR]

Churches struck by the earthquake sequence of 2016–2017 in Central Italy confirmed their seismic vulnerability, significantly higher than the one of other unreinforced masonry structures. This resulted in a much wider area affected by significant damages to churches, which were characterised by a rich variability of materials, typologies, dimensions and styles. In the area where significant damages were observed for ordinary buildings, most of the churches exhibited total or partial collapses. The time sequence of the main shocks helped in preventing casualties in churches although the collapse of a bell-gable in Accumoli caused victims in a neighbour house during the first event of August 24th, 2016. Damage surveys to churches were carried out on more than 4000 buildings, in a land area of about 30 000 km2 from September 2016 to May 2017. The data collected during the post-earthquake surveys represent a valuable source of information for better understanding the vulnerability of these structures as well as the effectiveness of past retrofitting interventions. Some examples are reported to show both damage progression due to the cumulated effect of repeated shaking and state-of-the-art strategies for short-term countermeasures. [ABSTRACT FROM AUTHOR]

This study proposes a methodology based on machine learning (ML) algorithms for rapid and robust classification of building structural types (STs) in multispectral remote sensing imagery aiming to assess buildings' seismic vulnerability. The seismic behavior of buildings is strongly affected by the ST, including material, age, height, and other main structural features. Previous works deployed in situ data integrated with remote sensing information to statistically infer STs through supervised ML methods. We propose a transferable methodology with specific focus on situations with imbalanced in situ data (i.e., the number of available labeled samples for model learning differs largely between different STs). We learn a transferable model by selecting features from an exhaustive set. The transferability relies on deploying geometric features characterizing individual buildings; thus, the model is less sensitive to domain adaption problems frequently induced by e.g., changes in acquisition parameters of remotely sensed imagery. Thereby, we show that few geometry features enable generalization capabilities similar to models learned with a large number of features describing spectral, geometrical or contextual building properties. We rely on an extensive geodatabase containing almost 18,000 building footprints. We follow a Random Forest (RF)-based feature selection strategy to objectively identify most valuable features for prediction. Furthermore, the problem of unbalanced classes is addressed by adopting two approaches: downsampling the majority class and modifying the classifier internally (weighted RF). The implemented model is transferred on the challenging urban morphology of the Val d'Agri area (Italy). Results confirm the statistical robustness of the model and the importance of the geometry features, allowing for reliable identification of STs. [ABSTRACT FROM AUTHOR]