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This deliverable reports an exhaustive state-of-the-art compilation of the most representative seismic fragility and loss estimation models for the buildings and infrastructure components in the testbeds (TBs in the following) of the TURNkey project, which are:TB1-Bucharest (Romania), TB2-Pyrenees (France), TB3-Hveragerði (Southern Iceland) and Húsavík (Northern Iceland), TB4-Patras and Aegio area (Greece), TB5-Port of Gioia Tauro (Italy), and TB6- Groningen (Netherlands).This activity is included within the Work Package 4, aimed at developing and harmonizing seismic physical vulnerability and loss estimation models for structures and infrastructure components within a rapid loss prediction framework. Within a broader context, it may be stated that the contents of this deliverable may also be extrapolated as a useful synthesis of the structural vulnerability standing for the entire European territory. In the chapter 2 of the document,adetailed list of the fragility and loss estimation models adopted for building taxonomies and infrastructure components is tabulated together with their associated publication/reference and a brief description of the corresponding work. Then, futher important information is syntesized in terms of type, structural typology, intensity measure, damage scale, and the region of applicability referring to each individual fragility/loss model under consideration. In chapter 3, in-depth information and discussion of the vulnerability and loss estimation models presented in Chapter 2 are provided for each TB.Furthermore, background exposure information is also provided. Finally, chapter 4 presents the conclusive summary of the Deliverable.

The global development of society requires constant updating of the objectives that education pursues and how they are achieved. Science education is an area undergoing advanced transformation, both at the level of objectives and methodologies, with a strong social, economic, and knowledge impact. Research-based education is a well-established term, especially in the higher education system. More studies and key policy documents argue that education must be based on cutting-edge research. Essential in this equation is the existence of dedicated frameworks (tools, events, courses, and strategies) and knowledgeable mentors and developers. Through reliable tools, we refer to real learning contexts created by the parties involved in studies and research together with those who analyze how students receive information at their level of knowledge and understanding. Such a context is also the integration platforms facilitating access to data, products, and research services. There are many such platforms, but not so many of them develop components dedicated to an important user category: pupils, students and their teachers. Considering this category of beneficiaries also means collecting feedback on what is relevant to them, what the platform exposes as information, and what actions they can take to be immersed in the research process. Future �Environmental Data Scientists� will need to draw on multiple data and information sources, using data analysis, statistics, and models to create knowledge that is communicated effectively to decision-makers in government, industry, and civil society. Platforms that �expose� monitoring data, offer access to research products, and allow both the interoperability and reproducibility of science and the transparency of the process leading to a shared outcome are essential for the much-claimed paradigm shift towards open science.

As part of the development of a European Seismic Risk Model 2020 (ESRM20), the spatial and temporal evolution of seismic design across Europe has been studied in order to better classify reinforced concrete buildings (which represent more than 30% of the approximately 145million residential, commercial and industrial buildings in Europe) and map them to vulnerability models based on simulated seismic design. This paper summarises the model that has been developed to assign the years when different seismic design levels (low code, moderate code and high code) were introduced in a number of European countries and the associated lateral forces that were specified spatially within each country for the low and moderate codes for typical reinforced concrete mid-rise buildings. This process has led to an improved understanding of how design regulations evolved across Europe and how this has impacted the vulnerability of the European residential building stock. The model estimates that ~ 60% of the reinforced concrete buildings in Europe have been seismically designed, and of those buildings ~ 60% have been designed to low code, ~ 25% to moderate code and 15% to high code. This seismic design model aims at being a dynamic source of information that will be continuously updated with additional feedback from local experts and datasets. To this end, all of the data has been made openly available as shapefiles on a GitLab repository.

The lockdown measures taken to control and stop the spread of the novel coronavirus (COVID-19) in cities around the globe caused an unprecedented reduction of anthropic activities. The signature of this reduction, different from one place to another, has been captured by the seismic stations installed in the urban areas where lockdown restrictions have been implemented. Bucharest, the capital of Romania, was no exception from this phenomenon.In this paper, we investigate the effect of the COVID-19 lockdown measures imposed by the Romanian authorities on the high-frequency ambient seismic noise (ASN) data recorded by the Bucharest Metropolitan Seismic Network (BMSN). BMSN consists of 26 stations of which 19 are equipped with strong motion sensors and 7 have both short-period velocity and accelerometer sensors. All the stations are continuously recording the ground motion and the data is sent in real-time to the data center of the National Institute for Earth Physics. The reduction of ASN was first observed at stations installed in educational units (kindergartens, schools) starting with 11th of March 2020, when the Romanian government decided to close the schools in Romania. For these stations, the largest reduction of ASN, up to 82%, was noticed in the 25-40 Hz frequency band. On 16th of March the state of emergency was imposed in Romania and a few days later, on 25th of March, the stay-at-home order was issued. These new restrictions caused substantial reduction in urban traffic and people’s mobility and reflected in significant reduction of ASN at almost all the other BMSN stations, located either free-field or in buildings. For these stations, we observed a decrease of the noise levels by as much as 66% in the 15-25 Hz frequency band. We also correlated the ambient seismic noise with other types of data that might be affected by human activity, such as the mobility data from Google and Apple, and we found good correlation between ASN in different frequency bands and various mobility data categories. Finally, we showed that the noise reduction due to lockdown measures improved the signal-to-noise ratio of the stations in the Bucharest area, allowing us to record smaller earthquakes which otherwise would not have been recorded.

The impact of natural hazards on structures and infrastructures is a critical issue that needs to be properly addressed by both public and private entities. To better cope with seismic hazard and to mitigate the risk, long-term multi-sensor infrastructure monitoring represents a useful tool for acquiring information on their condition and vulnerability. However, the current increasing data volume collected using sensors is not suitable to be processed with classical standalone methods. Thus, automatic algorithms and decision-making frameworks should be developed to use this data, with minimum intervention from human operators. A case-study for the application of advanced methods is focused on the headquarters of the Institute for Atomic Physics, a 11-story reinforced concrete building, located near Bucharest, Romania. The instrumentation scheme consists of accelerometers installed at the basement, at an intermediate floor and at the top of the structure. The data were continuously recorded, starting with December 2013. More than 80 seismic events with moment magnitude, MW, larger than 3.8 were recorded during the monitoring period. The current study covers the long-term evolution and variation of dynamic parameters (one value per hour), based on both ambient noise sources and small and medium magnitude seismic events. The seasonal variation of these parameters will be determined, as well as their daily variation and the differences between values obtained from ambient noise and from earthquake-induced vibrations. Other atmospheric parameters (e.g. temperature, precipitation, wind speed) will be considered in future studies. The goal of the PREVENT project, in the framework of which the research is performed, is to collect multi-disciplinary data and to integrate them into a complex monitoring system. The current study achieved the first step, focusing on data from the seismic sensors and setting up the premises for a multi-sensor, multi-parameter, more reliable infrastructure monitoring system.

The aim of this article is to analyze the background, current status, and outlook of seismic monitoring products and services in Bulgaria, Moldova, Romania, and Ukraine. These countries manage seismic networks that contribute to the European Integrated Data Archive node in the framework of the Observatories and Research Facilities for European Seismology, which represents a collaborative effort in coordinating observational seismology across the European region through the collection, archiving, and dissemination of seismic waveform data, metadata, and related products. All of the aforementioned countries share a common threat: strong earthquakes occurring in the Vrancea area located in central-eastern Romania at intermediate depths (usually in the 60–180 km interval). Events such as the ones on 10 November 1940 and 4 March 1977 generated high damage in Romania, northern Bulgaria, and Moldova. In addition to Vrancea, crustal earthquakes in areas such as Shabla or Dulovo can lead to cross-border damage. Therefore, understanding the way national seismic networks are distributed, how they cooperate, and the products and services that they provide in (near) real time and their terms is of significant interest in the context of necessary hazard harmonization and joint emergency intervention and risk mitigation actions.

The paper presents results from an experimental program implemented for three representative buildings in Bucharest metropolitan area and aimed to explore the potential of various dynamic identification methods in providing information about building state changes. The objective is to establish reference values of potential use in rapid earthquake damage detection systems. Each of the selected buildings was designed according to a different seismic code, in force at the time of its construction. The methods employed for this study were: the analysis of Fourier spectra, the analysis of the transfer function and the random decrement technique. To validate the results, the fundamental periods of vibration determined experimentally were compared with the corresponding values predicted by the empirical formulas specified in the corresponding editions of the Romanian seismic code. The results revealed consistent values for both the fundamental period and the damping ratio of the buildings. However, small variations of the two parameters were identified, depending on the time the recordings were performed, noise sources and levels and building occupancy. The results, in terms of validated data on the dynamic characteristics of Romanian building stock and of assessment of methods performance, add up to the information pool needed for the development of countrywide pre- and post-earthquake assisted decision tools.

Due to their widespread and continuous expansion, transportation networks are considerably exposed to natural hazards such as earthquakes, floods, landslides or hurricanes. The vulnerability of specific segments and structures such as bridges, tunnels, pumps or storage tanks can translate not only in direct losses but also in significant indirect losses at systemic level. Cascading effects such as post-event traffic congestion, building debris or tsunamis can contribute to an even greater level of risk. To support the effort of modelling the natural hazards implications at full transportation network scale, we developed a new applicable framework relying on (i) GIS to define, geo-spatially analyze and represent transportation networks; (ii) methods for determining the probability of network segments to fail due to natural hazard effects; (iii) MonteCarlo simulation for multiple scenario generation; (iv) methods (using Dijkstra algorithm) to analyze the implications of connectivity loss on emergency intervention times and transit disruption, (v) correlations with other vulnerability and risk indicators. Currently, the framework is integrated in ArcGIS Desktop as a toolbox (entitled Network-risk) – making use of the Model Builder functions and being free for download and customize. Network-risk is an attempt to bring together interdisciplinary research with the goal of creating an automated solution to deliver insights on how a transportation network can be affected by natural hazards, directly and indirectly, aiding in risk evaluation and mitigation planning. In this article we present and test Network-risk at full urban scale, for the entire road network of Bucharest – one of the world's most exposed capitals due to earthquakes, with high seismic hazard values and a vulnerable building stock, but also significant traffic congestion problems not yet quantified in risk analyses.

The real-time analysis of a structure’s integrity associated with a process to estimate damage levels improves the safety of people and assets and reduces the economic losses associated with interrupted production or operation of the structure. The appearance of damage in a building changes its dynamic response (frequency, damping, and/or modal shape), and one of the most effective methods for the continuous assessment of integrity is based on the use of ambient vibrations. However, although resonance frequency can be used as an indicator of change, misinterpretation is possible since frequency is affected not only by the occurrence of damage but also by certain operating conditions and particularly certain atmospheric conditions. In this study, after analyzing the correlation of resonance frequency values with temperature for one building, we use the data mining method called “association rule learning” (ARL) to predict future frequencies according to temperature measurements. We then propose an anomaly interpretation strategy using the “traffic light” method.

The paper presents results from a study on monitoring the long-term variation of the dynamic characteristics of an 11-story reinforced concrete building located near Bucharest. Since the deployment, in December 2013, of a permanent monitoring system, 89 seismic events with a moment-magnitude (MW) larger than 3.8 were reported. Out of these, 80 were recorded properly by the seismic sensors and the data was used to extract the fundamental frequency and the damping ratio of the building for each event. The main method used to compute the dynamic parameters was the Random Decrement Technique. A dependency of the resulting fundamental frequencies on the maximum accelerations at the base and on top of the building was observed. Due to the structural peculiarities, the fundamental frequency of the building on the transverse direction was lower than the one on the longitudinal direction, this being reflected also by the experimental results. The maximum drop in the fundamental frequency was reported for the MW=5.5 October 28th, 2018 seismic event. By performing this type of analyses, the dynamic parameters of buildings can be tracked over long periods of time and their variation under seismic excitation can be assessed, allowing rapid detection of structural health alterations.

The post-earthquake evaluation of structural integrity is a critical point to be addressed in case of emergency situations triggered by the occurrence of seismic events. A valuable method that can provide important indices to experts performing this operation is the monitoring of structures with seismic sensors that record how the structure responds to earthquake ground motion. In the case of permanent monitoring systems, reliable information can be obtained by comparing the data recorded before, during and after the earthquake, and checking if any abnormal vibrations of the structure or dynamic parameter changes have occurred. The presented study analysed comparatively, for an 11-story reinforced concrete building, vibration data recorded before, during and after the October 28th, 2018 earthquake (MW = 5.5). Continuously recorded data was used to determine the hourly values of the fundamental frequency of the building. The short-term behaviour (72 hours) was assessed, highlighting the modal parameters variation during, before and after the earthquake. In addition, an analysis of the data recorded one and a half hours before the earthquake and one and a half hours after the earthquake provided useful information on the evolution of the building state and on how this “recovered” after the earthquake.

Analyzing the integrity of a structure and implementing a process to estimate the level of damage in real time increase the safety of people and goods and reduce economic losses associated with the production interruption or operation of the structure. The appearance of damage to a building changes its dynamic response (frequency, damping and/or modal shape) and, therefore, one of the most effective methods for continuous assessment of integrity is based on the use of ambient vibrations. However, if the resonance frequency can be used as indicator of changes, a misinterpretation can be due to the fact that frequency is not only affected by the occurrence of damage, but also by certain operating conditions and especially certain atmospheric conditions. In this study, after analyzing the correlation of the resonance frequency values with temperature for one building, we used the data mining method called "association rule learning" (ARL) to predict the future frequency depending on the measured temperature. We then propose an interpretation strategy of anomalies using the method called "traffic-light".

The paper intends to evaluate and analyze the accelerometric data recorded on certain buildings located in the Bucharest metropolitan area, one of the most exposed in Europe, with three strong earthquakes with magnitude MW>7 in the last century. Starting from information comprised by databases for soils and buildings existing in Bucharest, certain types of structures were selected, according to their specificity (old buildings, retrofitted, etc.) and being continuously seismic monitored. The selected three buildings are equipped with seismic isolators and viscous dampers. The response of these structures, at the ground level, subjected to medium intensity earthquakes will be discussed in terms of peak accelerations and spectral accelerations. Based on the currently accepted standpoint that the dynamic response of certain structures subjected to earthquakes is strongly dependent of the ratio between the natural period of the structure and the dominant period at the construction site, a comparative analysis against free-field data is presented. There would be presented the improvement of seismic response of isolated buildings in Bucharest and the reason these buildings were protected choosing this method. The aim is to provide warnings regarding the severity of seismic events, by means of characteristics of the ground motion, gathered from the response spectra, which may be given soon after the seismic event took place. All the data recorded on instrumented structures during two seismic events (MW = 5.5 and MW = 4.8), together with the subsequent analysis, can represent a reference study for future earthquakes with similar magnitude. The integration of near-realtime seismology with performance-based earthquake engineering allows for providing the information useful for earthquake engineers and decision makers and can enhance the mitigation of seismic risk.