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Analytical expressions for the floor spectra evaluation play a key role in the correct definition of the seismic input induced to non-structural elements or local mechanisms in existing buildings. They have to be able properly assessing the possible amplification phenomena, but also correctly describing the effects of nonlinearities due to structural damage. Due to the complexity of such phenomena, data on existing structures hit by earthquakes constitute a precious source for a better understanding of the topic and the validation of analytical expressions. In this framework, the paper aim is twofold. On one hand, it evaluates the entity of seismic amplification through experimental evidences from in-situ measurements on two existing monitored unreinforced structures. On the other hand, it presents the application on them of an analytical expression for the floor spectra already developed by the Authors. The case-studies are the former courthouse of Fabriano (Ancona, Italy) and the Pizzoli's town hall (L'Aquila, Italy). They were both hit by the 2016/2017 earthquake in Central Italy and are permanently monitored by the Italian seismic monitoring system of the Italian Department of Civil Protection. With the aim of validating the above-mentioned expression, the paper shows the comparison between experimental and analytical floor spectra for various minor events and mainshocks of the Central Italy earthquake. Since the two case-studies exhibited different damage levels (from slight to moderate, respectively), the comparison allowed us to verify the reliability of the expression both in the pseudo-elastic and moderate nonlinear fields. [ABSTRACT FROM AUTHOR]

In mountainous areas, snow avalanches could be triggered by the shaking produced by earthquakes. The forces induced by the earthquake can cause an irregular increase of shear strength load down the slope, for the presence of complex surface and buried morphologies. Topographic irregularities generate maximum effects of waves amplification linked to wavelengths comparable to the horizontal dimension of the topographic feature. For this reason, the selected time-histories represent an appropriate input for the two-dimensional numerical response analyses when a dynamic phenomenon produce the resonant motion of a whole mountain. This represents an important earthquake-induced hazard in snow-covered mountain areas with high probability of seismic events. Some valleys are located in regions with scare ground motion data and investments on infrastructures are not always accompanied by adequate protection against earthquake-induced avalanches. The paper points out a simple deterministic approach for selecting a set of real accelerograms applied to a real case of Siella Mountain (Central Italy) where a large avalanche destroying a tourist facility of Rigopiano resort on 18 January 2017. The selected time histories were used as input for the two-dimensional numerical model of the subsoil to evaluate the topographic seismic amplification in ridge and compare it with the results of other authors. These methods suggest that morphology-related inertial effects should be considered as an overload action on snow layers when controlling multi-hazard studies and spatial planning. [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]

This paper presents a novel hybrid-based methodology devoted to develop urban fragility curves and damage probability matrices to predict likelihood seismic damage scenarios for small and medium Italian urban centres, considering URM buildings only. The concept of urban fragility curve consists of a single curve mean-representative of the seismic fragility of an entire area accounting for the combinations of building classes and their percentage, then they differ from those typological. The methodology has been developed with reference to Rocca di Mezzo, a small Italian urban centre located in the central Apennine area, Italy. Based on CarTiS inventory, building classes have been firstly recognized and urban fragility curves, representative for damage scenarios at Ultimate Limit State, developed. To predict damage scenarios from low to high-intensity earthquakes, an approach to define multi-damage urban fragility curves and damage probability matrices has been also presented. To this aim, a damage scale suffered by building classes has been defined by converting the final outcomes of the AeDES form (used in Italy for post-earthquake surveys) in the damage levels provided by the European Macroseismic Scale (EMS98). Data coming from urban fragility curves have been compared with the actual damage scenario recorded in Rocca di Mezzo after the 2009 L'Aquila's earthquake, in terms of both peak-ground acceleration and Mecalli-Cancani-Sieberg scale. The achieved results showed a good accordance between theoretical predictions and actual damage scenarios, coherent also with the damage scenarios occurred in other Italian historical centres hit by severe earthquakes over the years. Thus, the methodology can provide a first important indicator to support the development of emergently plans devoted to identify priority of interventions in such areas particularly vulnerable with respect to others. [ABSTRACT FROM AUTHOR]

Drawing on socio-psychology and economics literature contributions, this paper provides an original conceptual framework examining whether and how natural disasters exert any influence on nuptiality. Scholars suggest that disasters remind people about the transience of life and mortality. This feature triggers shifting towards intrinsic meaningful goals — such as commitment to relationships; at the same time, it fosters people's proximity and support-seeking from their security providing attachment figures and leads to accelerate life transition choices. In this view, disasters are expected to positively impact on people's intentions to marry. Such an effect is evident in case of natural hazards determining slight damage to physical capital (buildings, productive locations, etc.) which have limited economic consequences that do not hamper marriage intentions. Meanwhile, in the case of highly disruptive disasters, these positive psychological pushes are counterbalanced or even exceeded by the negative economic consequences of the disaster, which inhibit marriage intentions. These predictions are supported by an empirical analysis that relies on a difference-in-differences investigation of municipality-level nuptiality data collected in the Abruzzo region of Italy before and after the major 2009 L'Aquila earthquake. [ABSTRACT FROM AUTHOR]

On April 6, 2009, a strong earthquake (6.1 Mw) struck the city of L'Aquila, which was severely damaged as well as many neighboring towns. After this event, a digital model of the region affected by the earthquake was built and a large amount of data was collected and made available. This allowed us to obtain a very detailed dataset that accurately describes a typical historic city in central Italy. Building on this work, we propose a study that employs machine learning (ML) tools to predict damage to buildings after the 2009 earthquake. The used dataset, in its original form, contains 21 features, in addition to the target variable which is the level of damage. We are able to differentiate between light, moderate and heavy damage with an accuracy of 59%, by using the Random Forest (RF) algorithm. The level of accuracy remains almost stable using only the 12 features selected by the Boruta algorithm. In both cases, the RF tool showed an excellent ability to distinguish between moderate-heavy and light damage: around the 3% of the buildings classified as seriously damaged were labeled by the algorithm as minor damage. [ABSTRACT FROM AUTHOR]

Stress adjustment and resilience after multiple natural disaster exposure, specifically two successive earthquakes (i.e. 2009 and 2016 earthquakes) have been investigated in persons with mental disorder and compared to a clinical sample evaluated after the first seismic 2009 event. Seventy-one persons referred to the Mental Health Service of L'Aquila for psychotic, mood and anxiety disorders, were evaluated for 'bounce back resilience' (BRS) and subjective adjustment after the 2016 natural disaster, the earthquake that hit Central Italy. They had already been exposed to a previous natural disaster, the earthquake that hit L'Aquila in 2009 (i.e. '2009/2016 sample'). The 2016 evaluations have been compared to that previously obtained at the 2009 event in an independent clinical sample (i.e. '2009 sample'). A relevant lower number of persons refer a good adjustment after the second natural disaster when compared to the assessment performed on the independent clinical '2009 sample'. After the second natural disaster, the total sample showed no differences in BRS scores compared to the 2009 sample. However, when diagnoses were taken into account, the highest BRS scores were observed in the sample of persons with psychoses and mood disorders in the '2009/2016 sample'. In contrast, those with anxiety disorders showed the lowest one. Among mental health service clients hit twice by a natural disaster in seven years, those with anxiety disorders are 'sensitized' to the trauma, therefore susceptible of more problematic adjustment. [ABSTRACT FROM AUTHOR]