The presence of historic centres in earthquake prone areas poses a number of challenges, which belong to collective memory but dramatically re-emerge after each severe seismic event. The high vulnerability of the building stock, especially of old masonry structures, has caused fatalities and structural collapses (Indirli et al., 2013; Penna, 2015; Dolce and Goretti, 2015; Sorrentino et al., 2019; Göçer, 2020), involving entire villages (Rapone et al., 2018; Sorrentino et al., 2019), ordinary buildings and aggregates (Penna et al., 2014; Vlachakis et al., 2020), and architectural heritage (Lagomarsino, 2012; D’Ayala and Paganoni, 2011; Cattari et al., 2014; Borri et al., 2019; Penna et al., 2019). It has also required many people to leave their own towns and move elsewhere, with further indirect troubles for the social identity and the economy of the communities (European Environment Agency, 2010).
The state of emergency immediately after the earthquake, during which people are rescued, dangerous buildings are secured and the safety of buildings is assessed, is followed by the much longer phase of reconstruction and structural retrofitting, which aims at repopulating places, restoring the beauty of architectural heritage, and restarting productive activities. At this stage, enhancing the safety level of the constructions in view of future earthquakes is a primary concern (Aguado et al., 2018; Mazzoni et al., 2018; Sisti et al., 2019). At the same time, it is of the utmost importance that the complex process of post-earthquake reconstruction progresses smoothly and it is completed with the available resources in a reasonable time (Di Ludovico et al., 2017).
In Italy, the institutions in charge of managing this process, together with research centres, universities and practitioners, have gained an outstanding expertise and developed effective procedures, such as the AEDES form for building usability (Baggio et al., 2007). On the other hand, after each of the recent earthquakes, the tools for damage survey and vulnerability assessment have been modified or re-formulated from scratch. Even for the same event, if the territory struck by the earthquake depends on multiple administrative bodies different methods have (or are currently being) used. For instance, after 2009 L’Aquila earthquake, the reconstruction of the municipality of L’Aquila and that of the other municipalities of the earthquake area are managed by two offices, which do not share the same tools. Likewise, after the 2016–2017 Central Italy earthquake, four administrative Regions are managing reconstruction through four offices, adopting different procedures.
There is no shortage in the scientific literature of methods for vulnerability assessment of unreinforced masonry structures. D’Ayala and Speranza (2002) proposed one of the first ones, named Failure Mechanism Identification and Vulnerability Evaluation (FaMIVE), which identifies the most probable collapse mechanisms based on 42 parameters related to wall geometry, openings, connection with orthogonal walls, floors and roof, and presence of tie-bars and ring beams. An electronic form calculates the horizontal load that triggers the onset of the mechanism through limit analysis and estimates the seismic vulnerability of the construction. As the very final output, four vulnerability classes are defined, such as low, medium, high and very high.
The Italian Group for the Protection against Earthquakes (Gruppo Nazionale per la Difesa dei Terremoti, GNDT) developed a method based on 11 parameters, including type, strength and arrangement of the masonry, floors and roof, vertical and horizontal layout, non-structural members, and damage state. The scores attributed to such parameters are combined in a weighted sum to derive an index between 0 and 100 (Dolce et al., 2005). The method was initially conceived for isolated buildings and then extended to aggregates adding 5 more parameters accounting for interactions between adjacent structures (Formisano et al., 2011).
The Special Office for the Reconstruction of L’Aquila (Ufficio Speciale per la Ricostruzione de L’Aquila, USRA) adopted a method based on 9 main parameters (USRA, 2014). A score is assigned to each of them and an electronic sheet calculates a vulnerability index comprised between 8 and 57. Vulnerability is then classified as low if the index is ≤ 20, medium if it is in the 21 ÷ 39 range, and high if it is ≥ 40. The vulnerability class is used, together with the damage level according to the EMS98 scale (European Seismological Commission, 1998), to calculate the maximum permissible financial contribution per square meter. Finally, the Special Office for the Reconstruction of the other municipalities (all except L’Aquila) struck by the 2009 earthquake (Ufficio Speciale per la Ricostruzione dei Comuni del Cratere, USRC) is using a similar procedure, but with different scores.
All these methods share many of the parameters to be surveyed and collected in a form to evaluate seismic vulnerability. Indeed, despite the specificities of the building stock, which may change form territory to territory, the main features of unreinforced masonry constructions and of their seismic response generally recur (Taffarel et al., 2018). The time is ripe for developing a standard method, treasuring from the lessons learned in the past, recent scientific outcomes, and the experience gained in the field.
This paper proposes a tool for the expeditious assessment of the seismic vulnerability of unreinforced masonry structures, which can be used in post-earthquake reconstruction. The method originates from those adopted by USRA (2014) and by GNDT (Formisano et al., 2011), which have already been extensively used after recent earthquakes, and appear more suitable than others for the management of reconstruction activities. The parameters included in these two methods were reassessed and recalibrated. Information is to be gathered on 10 structural features, including the effectiveness of connections, the constructive details, the characteristics of floors and roof, the interaction with non-structural elements, and the quality of masonry. The role of this latter, which is accounted for only qualitatively in current practice, was evaluated quantitatively through the Masonry Quality Index (Borri et al., 2015), which considers constituent materials, size and shape of the units, thickness of the joints, and arrangement, and proves in good agreement with results of field tests. An expeditious survey is sufficient for a practitioner to collect required data on a building, which are combined to calculate a vulnerability index in the 0 ÷ 100 range. For calibration and validation, the correlation of such vulnerability index with an empirical damage index was calculated through a regression analysis on a sample of 50 masonry aggregates, including nearly 200 structural units, in the historic centres of L’Aquila and of the hamlets nearby. The sample was selected to be representative of the built heritage of the area as well as of many other earthquake prone areas in Italy, such as those struck by the recent 2016–2017 Central Italy earthquake (Penna et al., 2019; Sisti et al., 2019; Sorrentino et al., 2019) and in many other European Countries.
The paper is organized as follows. The proposed method is presented in § 2; the ten structural parameters to survey are listed together with the scores attributed to each of them, which are summed to calculate the Vulnerability Index. The parameters are described one by one in § 3, which also provides a brief roadmap for the evaluation of each of them, with the only exception of the quality of masonry, which is dealt with in depth later. Section 4 describes the sample of structural units selected for the calibration and validation of the proposed method in this study, its properties and the damage state of the buildings as reported in post-earthquake surveys. Section 5 describes the calibration of the scores attributed to the ten structural parameters and shows the correlation between the resulting vulnerability index (calculated for arch structural unit of the sample) and the corresponding damage index. Finally, the role of the quality of masonry and the use of the Masonry Quality Index (Borri and De Maria, 2009b; Borri et al., 2015; Borri and De Maria, 2019) for its quantification is discussed in § 6.