Valeria Leggieri

Structural diagnostics of buildings require optimization of investigation methods to minimize invasiveness, save time, and reduce costs. In this view, non-destructive tests, such as ultrasonic and sonic tests, are essential tools. However, it is crucial to reduce and properly locate the more laborious and/or destructive tests, to enhance the diagnostic campaign efficiency, particularly if buildings are in use, to ensure the occupants' well-being. While direct ultrasonic measurements provide precise data, they often require more invasive procedures and provide punctual information. In contrast, sonic tests, which can be performed using reflection techniques, require only surface access and are less invasive, providing valuable information when compared with direct ultrasonic data. In the framework of the MULTICLIMACT project, sonic and ultrasonic tests were conducted on some columns: the results were compared with each other, to validate the proposed methodology.

In recent years, innovative Non-Destructive Testing (NDT) techniques, applicable for the assessment of existing civil structures, have become available for in situ analysis on Reinforced Concrete (RC) and masonry structures, but they are still not established for regular inspections, especially after seismic events. The damage assessment of RC buildings after seismic events is a very relevant issue in Italy, where most of the structures built in the last 50 years are RC structures. Furthermore, there is also a growing interest in being able to monitor structural health aspects by storing them on the building’s digital twin. For these reasons, it is necessary to develop an affordable and ready-to-use NDT procedure that provides more accurate indications on the real state of damage of reinforced concrete buildings after seismic events and to integrate these data into an interoperable digital twin for automated, optimized building performance monitoring, management, and preventive maintenance. To this end, a case study was conducted on a building in the Marche region in Italy, damaged by the 2016 earthquake. Non-destructive tests were performed and inserted into the LIS platform for the creation of a digital twin of the building. This platform seamlessly manages, visualizes, and analyzes the collected data and integrates various sensor nodes deployed throughout the building. The paper also presents a methodology to simplify the work of the test operator and make the entire process of knowledge of the building faster and more sustainable through a QR-code interface.

The paper presents a methodology of extraction, integration and elaboration of data from different sources using the geographic information system (GIS), to realize a georeferenced building database (GBD) useful for the seismic vulnerability assessment of existing buildings on a large scale. Three levels of GIS entities have been defined and equipped with the related information: census section (CS), urban block (UB), and individual building (IB), depending on the level of detail of dataset. Additional information about the typological and structural features has been extracted by CARTIS catalogue, to refine the data associated with each building. The data have been validated using detailed information gathered on a proper sample of buildings, which have been filed and analyzed one-by-one. The alphanumeric format of data allows for the automatic implementation of different methods available in the literature, which provide a qualitative seismic vulnerability index at different scales (whole urban district, an urban block, and a single building). Finally, the 3D representation of data and results have been elaborated, providing a tool easily searchable and constantly implementable. An application has been developed for a case study in Puglia, Italy: Bisceglie, for which 3726 IB have been assessed. The work addresses the issue of the lack of information typical of large-scale applications, exploiting all the available data sources to achieve nearly complete knowledge of existing building stock finalized to a rapid but extensive evaluation of the seismic vulnerability on an urban scale with very low computational efforts and the use of limited resources in terms of time and cost.

The paper presents View VULMA, a data set specifically designed for training machine-learning tools for elaborating fast vulnerability analysis of existing buildings. Such tools require supervised training via an extensive set of building imagery, for which several typological parameters should be defined, with a proper label assigned to each sample on a per-parameter basis. Thus, it is clear how defining an adequate training data set plays a key role, and several aspects should be considered, such as data availability, preprocessing, augmentation and balancing according to the selected labels. In this paper, we highlight all these issues, describing the pursued strategies to elaborate a reliable data set. In particular, a detailed description of both requirements (e.g., scale and resolution of images, evaluation parameters and data heterogeneity) and the steps followed to define View VULMA are provided, starting from the data assessment (which allowed to reduce the initial sample of about 20.000 images to a subset of about 3.000 pictures), to achieve the goal of training a transfer-learning-based automated tool for fast estimation of the vulnerability of existing buildings from single pictures.

The study of the seismic vulnerability of historical centres, especially in the Mediterranean zone, is one of the main issues in ongoing scientific research. This is due, on the one hand, to the continuous evolution of the seismic demand and, on the other hand, to the high vulnerability of the masonry existing building stock. The seismic events of the last few years highlighted the necessity to perform a large-scale survey of the huge amount of masonry buildings in historical centres, in order to provide prioritization scales for planning mitigation strategies. With this regard, the scientific literature provides several methodologies that allow a rapid assessment based on pre- defined survey forms. The data obtained from the surveys are usually used as the input for algorithms aimed at estimating the vulnerability level of the building investigated. The aim of the present work is to propose a general framework for analysing seismic vulnerability of masonry historical centres and deriving fragility curves basing on multiple data sources. In particular, using data collected through existing territorial databases, supplemented by a set of vulnerability forms available for the city centre of the Municipality of Foggia, Southern Italy, some vulnerability classes are defined. Based on the mechanical and geometrical features identified for each class, several ideal and representative buildings are generated, and their seismic behaviour is investigated through the variation of significant parameters. At the end, the capacity of the buildings is evaluated by performing simplified nonlinear analyses and, subsequently, by estimating the damage level of the sample through the definition of regional fragility curves.

The paper describes the numerical approach adopted to investigate the effects of vibrations induced on reinforced concrete (R.C.) buildings by the excavation works needed to bury an existing railway line crossing an urban area in the south of Italy. The construction works are carried out in dolomitic rocks, characterized by a high resistance to excavation. Therefore, they may have a great impact on the surrounding environment in terms of induced vibrations. The study is conducted through an uncoupled approach, investigating the dynamic response of the geotechnical system and the above-surface structure, separately. The impulse force equivalent to the dynamic action of a breaker hammer is used as input motion for 2D finite element (FE) geotechnical simulations of the wave propagation process occurring during the excavation. Then, the acceleration time histories obtained from the geotechnical analyses are adopted to study the dynamic performance of an “index” R.C. building, representing the most recurrent structural typology in the examined area, through a 3D FE model. The results show how the adoption of a mitigation strategy consisting in the execution of a preliminary vertical cut followed by a rock crushing treatment allows to significantly reduce the vibrations induced by the excavation processes on existing buildings.