Structures inevitably suffer damages after an earthquake, with their severity ranging from minimal damages to non-structural elements to partial or even total collapse, possibly with loss of human lives. Thus, it is essential for engineers to understand the crucial factors that drive a structure towards suffering higher degrees of damage, so that preventative measures can be taken. In the present study, we focus on three well-known damage thresholds, namely Collapse Limit State, Ultimate Limit State and Serviceability Limit State and analyze which of the features obtained via Rapid Visual Screening, determine whether or not a given structure will cross that threshold. To this end, we use Machine Learning to perform binary classification for each damage threshold, as well as Explainability via SHAP values (acronym for SHapley Additive exPlanations) to quantify the effect of each parameter. The quantitative results obtained demonstrate the potential applicability of ML methods to re-calibrate the computation of structural vulnerability indices using data from recent earthquakes.

The elastic wave equation with the seismic tensorial force is solved in a homogeneous and isotropic medium (the Earth). Spherical-shell waves are obtained, which are associated to the primary P and S seismic waves. It is shown that these waves produce secondary waves with sources on the plane surface of a half-space, which have the form of abrupt walls with a long tail, propagating in the interior and on the surface of the half-space. These secondary waves are associated to the seismic mainshock. The results, previously reported, are re-derived by using Fourier transformations and specific regularization procedures. The relevance of this seismic motion for the ground motion, the seismographs' recordings and the effect of the inhomogeneities in the medium are discussed.

This study investigates the effectiveness of a range of timber-based solutions for seismic and energy retrofitting of existing masonry buildings. These solutions are designed not only to prevent structural collapse during earthquakes but also to create integrated interventions that enhance thermo-physical performance and reduce emissions in existing buildings. Various case scenarios were considered and both mechanical and energetic behavior post-intervention were evaluated. Timber-engineered products serve as foundational components for the retrofit approach, encompassing one-dimensional vertical elements (strong-backs) and various types of panels (cross-laminated timber panels, laminated veneer lumber panels, and oriented strand board panels). The analyzed retrofit techniques share a common principle, involving the attachment of these timber-based elements to the building's wall surfaces through mechanical point-to-point connections. The proposed solutions integrate strong-backs and timber panels with membranes and insulation layers, yielding cohesive and highly effective interventions. Finite element modeling was employed to analyze the mechanical and thermal responses of the retrofitted walls. A comprehensive comparative analysis of various techniques was conducted to determine the most effective solution for each specific scenario.

The statistical analysis of impact of the top 50 solar flares of X-class (1997-2023) on the global seismic activity, as well as on the earthquake preparation zones located in illuminated part of the globe and in the area of 5000 km radius around the subsolar point was carried out. It is shown by a method of epoch superposition that for all cases the increase of seismicity is observed, especially in the region around the subsolar point (up to 38%) during 10 days after the solar flare in comparison with preceding 10 days. The case study of aftershock sequence of strong M=9.1 earthquake (Su-matra-Andaman Islands, 26.12.2004) after the solar flare of X7.2 class (20.01.2005) demonstrated that the number of aftershocks with magnitude M≥2.5 increases more than 20 times after the solar flare with a delay of 7 days. For the case of the Darfield earthquake (M=7.1, 04.09.2010, New Zealand) it was shown that strong solar flares of class X and M probably triggered two strong aftershocks (M>6) with the same delay of 6 days on the Port Hills fault, which is the most sensitive to external electromagnetic impact from point of view of the fault electrical conductivity and orientation. Based on the obtained results the possible application of natural electromagnetic triggering of earthquakes is discussed for a short-term earthquake prediction using confidently recorded strong external electromagnetic triggering impacts on the specific earthquake preparation zones, as well as ionospheric perturbations due to aerosol emission from the earthquake sources recorded by satellites.

A reliability-based criterion to estimate strength amplification factors for buildings with asymmetric yielding located within a seismic region presenting different soil conditions is proposed and applied. The approach involves the calculation of the mean annual rate of exceedance of structural demands of systems with different levels of asymmetric yielding. Two simplified mathematical expressions are developed considering different soil conditions of the valley of Mexico. The mathematical expressions depend on the ductility of the structural systems, their level of asymmetric yielding, their fundamental vibration period and the dominant period of the soil. In addition, the proposed expressions are compared with that recommended by the current Mexico City Building Code (MCBC). Since the expressions are developed with the help of simplified structural systems, the validity of such expressions is corroborated by comparing the expected ductility demand of multi-degree of freedom (MDOF) structural systems with respect to that of their equivalent simplified systems. Both structural representations are associated with a given annual rate of exceedance value of an engineering demand parameter. The expressions proposed in this study will be incorporated in the new version of the MCBC.

We use earthquake ground motion modelling via Ground Motion Prediction Equations (GMPEs) and numerical simulation of seismic waves to consider the effects of site amplification and basin resonance in Jakarta, the capital city of Indonesia. While spectral accelerations at short periods are sensitive to near-surface conditions (i.e., Vs30), our results suggest that, for basins as deep as Jakarta’s, available GMPEs cannot be relied upon to accurately estimate the effect of basin depth on ground motions at long periods (>1 s). Amplitudes at such long periods are influenced by entrapment of seismic waves in the basin, resulting in longer duration of strong ground motion, and interference between incoming and reflected waves as well as focusing at basin edges may amplify seismic waves. In order to simulate such phenomena in detail, a basin model derived from a previous study is used as a computational domain for deterministic earthquake scenario modeling in a 2-dimensional cross-section. A M_w 9.0 megathrust, a M_w 6.5 crustal thrust and a M_w 7.0 instraslab earthquake are chosen as scenario events that pose credible threats to Jakarta, and the interactions with the basin of seismic waves generated by these events were simulated. The highest PGV amplifications are recorded at sites near the middle of the basin and near its southern edge, with maximum amplifications of PGV in the horizontal component of 200% for the crustal, 600% for the megathrust and 335% for the deep intraslab earthquake scenario, respectively. We find that the levels of ground motion response spectral acceleration fall below those of the 2012 Indonesian building Codes's design response spectrum for short periods (< 1 s), but closely approach or may even exceed these levels for longer periods.

To study the strengthening effect on recycled concrete columns by carbon fiber composite materials (CFRP) under different levels of seismic damage, four column specimens were designed for pseudo-static tests. The four specimens were respectively non-destructive without strengthening (prototype), non-destructive strengthening, medium seismic damage strengthening and severe seismic damage strengthening, according to the replacement rate of recycled aggregates and the level of seismic damage. The characteristics of the deformation damage and seismic performance indicators of each specimen were compared and analyzed. A decrease was observed in the initial stiffness of the seismically damaged recycled concrete column specimens strengthened with CFRP, while the ductility, peak bearing capacity and energy dissipation capacity of the specimens were improved. On the other hand, with the reduction of seismic damage and the increase of recycled aggregate replacement rate, the ductility and energy dissipation capacity of the reinforced seismic damaged recycled concrete column specimens were enhanced to different levels. In particular, the cumulative energy consumption of the strengthened specimens under medium seismic damage increased most significantly by 32.5%. In general, the hysteretic curves of the strengthened specimens were full, and the average ductility coefficients were 4.1–6.8. CFRP strengthening was more effective in restoring and enhancing the performance of the recycled concrete column specimens with medium and lower seismic damage levels (displacement ratio ≤ 3%).

The problems of formation and propagation of surface seismic waves in vertically layered and horizontally inhomogeneous media are studied. A mathematical model has been developed for the propagation of surface seismic waves in an inhomogeneous medium based on the use of the fundamental principles of wave dynamics and Fourier transforms. The existence of various types of groups of these waves is proved, and their main properties are studied. It has been established that the reflection coefficients of different groups of a dispersive wave on models of half-spaces (a layered, inhomogeneous medium) with a sharp velocity differentiation are characterized by the same dependence on the angle of incidence as in the absence of dispersion. In the region of the critical angle, which depends on the period of the incident wave, a local decrease in the intensity of wave reflection is observed, which is associated with the origin of the head dispersive wave. It has been found that the reflection coefficients of Rayleigh waves from low-velocity layers, thin (d / λ2 = 0.205) and thick (d / λ2 = 0.82) are approximately 0.2 ± 0.04 and practically do not change with increasing angle of incidence. On the basis of theoretical studies, it was revealed that reflected surface waves carry information both about the elastic properties of the reflecting medium and about the dimensions of the reflecting horizontal inhomogeneity. An experimental dispersion curve of the group velocity of Rayleigh waves on the Central Asia-Caucasus path has been obtained. The seismic stress state of the "subgrade-base" system was studied. Based on the analysis of the results of numerical experiments, it has been established that in order to obtain a complete picture of the seismically stressed state of the subgrade, it is necessary to take into account the contribution to it of each component of the accelerogram of a real earthquake.

MzSTools is a plugin for QGIS developed by the Institute of Environmental Geology and Geoengineering of the National Research Council (CNR-IGAG). The plugin has been designed as a set of practical and easy-to-use tools to carry out seismic microzonation (SM) studies, by producing standard compliant geographic database and maps, thus making them accurate, homogeneous and uniform for all municipalities in Italy. A geodatabase based on SQLite/SpatiaLite Relational Database Management System (RDBMS) has been designed to collect and store data related to elements such as: geognostic surveys; bedrocks and cover terrains; superficial and buried geomorphological elements; tectonic-structural elements; elements of geological instability such as landslide zones, liquefaction zones and zones affected by active and capable faults; homogeneous microzones in seismic perspective, microzones characterized by a seismic amplification factor. MzSTools assembles in a single software environment a set of useful tools in a configurable QGIS project template, comprising layers, symbol libraries, cartographic styles and print layouts for the SM maps. The plugin is open source and hosted on the GitHub platform, and available via the official QGIS plugins repository (https://plugins.qgis.org/plugins/MzSTools/).

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

Seismic velocity inversion is one of the most critical issues in the field of seismic exploration and has long been the focus of numerous experts and scholars. In recent years, the advancement of machine learning technologies has infused new vitality into the research of seismic velocity inversion and yielded a wealth of research outcomes. Typically, seismic velocity inversion based on machine learning lacks control over physical processes and interpretability. Starting from wave theory and the physical processes of seismic data acquisition, this paper proposes a method for seismic velocity model inversion based on Physical Embedding Recurrent Neural Networks. Firstly, the wave equation is a mathematical representation of the physical process of acoustic waves propagating through a medium, and the finite difference method is an effective approach to solving the wave equation. With this in mind, we introduce the architecture of recurrent neural networks to describe the finite difference solution of the wave equation, realizing the embedding of physical processes into machine learning. Secondly, in seismic data acquisition, the propagation of acoustic waves from multiple sources through the medium represents a high-dimensional causal time series (wavefield snapshots), where the influential variable is the velocity model, and the received signals are the observations of the wavefield. This forms a forward modeling process as the forward simulation of the wavefield equation, and the use of error back-propagation between observations and calculations as the velocity inversion process. Through time-lapse inversion and incorporating the causal information of wavefield propagation, the non-uniqueness issue in velocity inversion is mitigated. Through mathematical derivations and theoretical model analyses, the effectiveness and rationality of the method are demonstrated. In conjunction with simulation results for complex models, the method proposed in this paper can achieve velocity inversion in complex geological structures.

The correlations of seismic noise, recorded during 1997-2022 at 229 stations around the world are investigated. The property of waveforms, known as the Donoho-Johnston threshold, is analyzed, which separates the absolute values of the orthogonal wavelet coefficients into "small" and "large". Network of 50 reference points is considered. For each reference point, a time series with a time step of 1 day is calculated as the median of the values of the DJ index from the 5 nearest stations. For each reference point, the correlations between the values of the DJ index at other reference points are calculated in a sliding time window of 365 days. Average values of the DJ index decrease, which is interpreted as indicators of global seismic hazard increasing. The maximum distances between reference points with strong correlations show an explosive increase after 2011. Bursts in the mean coherences between the length of day (LOD) and the values of the DJ index at the reference points precede the release of seismic energy with a delay of about 530 days. High amplitude of the DJ index response to LOD for the times 2020-2022 was identified, which may forecast a strong earthquake in the second half of 2023.

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific seismic improvement interventions and emergency management plans. Unappropriate seismic risk assessments may provide misleading results and induce bad decisions with relevant economic and social impact.The seismic risk in urban areas is mainly linked to three factors, namely, “hazard”, “exposure” and “vulnerability”. Hazard measures the potential of an earthquake to produce harm; exposure evaluates the amount of population exposed to harm; vulnerability represents the proneness of considered buildings to suffer damages in case of an earthquake. Estimates of such factors may not always coincide with the perceived risk of the resident population. The propensity to implement structural seismic improvement interventions aimed at reducing the vulnerability of buildings depends significantly on the perceived risk.This paper investigates on the difference between objective and perceived risk and highlights some critical issues. The aim of this study is to calibrate opportune policies, which allow addressing the most appropriate seismic risk mitigation options with reference to current levels of perceived risk. We propose the introduction of a Seismic Policy Prevention index (SPPi). This methodology is applied to a case-study focused on a densely populated district of the city of Catania (Italy).

In this work the seismic resilience of the Emergency Department of a real Hospital complex, located in Tuscany (Italy), has been quantified, with special reference to its nonstructural components and organizational features. Special attention has been paid to the ceilings, whose importance stood out in past earthquakes. A comprehensive meta-model has been set, able to relate all the considered parameters to the assumed response quantity, i.e. the waiting time of the red-code patients arriving to the Emergency Department in the hours immediately after the seismic event. The seismic resilience of the Emergency Department has been measured with reference to earthquakes compatible to the seismic hazard of the area.

Fault detection is an important step for subsurface interpretation and reservoir characterization from 3D seismic images. Due to the numerous and complicated faulting structures of seismic images, manual seismic interpretation is time taking and need intensive work. To overcome this problem, geoscientists are coming up with productive computer-aided techniques for assisting in interpreter science for many years. However, in this paper, we used a pre-trained CNN model to predict faults from the 3D seismic volume of the Poseidon field of Browse Basin, Australia. Basically, this field is highly structured with complex normal faulting throughout the targeted Plover Formations. So, our motivation for this work in this field is to compare machine learning-based fault prediction to user interpreted faults identification with supported by seismic variance attribute. We found very satisfying result using DL with having an improved fault probability volume that outperform variance technology. Therefore, we propose that this workflow could reduce time and able to predict fault quite accurately in any field area.

The analysis of the radon-seismicity relationship has been carried out so far in the Vrancea (Ro-mania) seismic zone, with monitoring stations positioned on tectonic faults. The article analyzes the evolution of radon under the conditions of the existence of deep and surface seismicity and the presence of mud volcanoes along with live fires caused by gases emitted from the soil. The monitoring area was extended to the Black Sea and the area of the Făgăraș Câmpulung fault, where a special radon detection system was set up, which was proposed for patenting. A case study is the effect of the earthquakes in Turkey (7.8 R and 7.5 R on 2023/02/06) on the seismically active areas in Romania in terms of gas emissions (radon, CO2). The main analysis methods on radon (we also included CO2) are applied to integrated time series and the use of anomaly detection algorithms. Data analysis shows that the effects of global warming introduce deviations in seasonal gas emissions compared to previous years. This makes it difficult to analyze the data and correlate them with seismicity. The main conclusions related to the development of a radon monitoring network and in general the emission of gases in seismic areas refer to the importance of the choice of equipment, the monitoring location and the installation method.

Mediterranean Ridge accretionary complex (MAC) is one of the most critical subduction zones in the world. It is known that the region exhibits a continuous mass change (horizontal/vertical movements). This process is associated with the devastating and tragic earthquakes shaking the MAC for centuries. Here, we investigate the ocean bottom pressure (OBP) anomalies in the MAC derived from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) satellite missions. The OBP time series for the MAC comprises a decreasing trend in addition to 1-, 1.53-, 2.36-, 3.67-, and 9.17-year periodic components partially explained by the atmosphere, oceans, and hydrosphere (AOH) processes, and Earth's pole movement. We noticed that the OBP anomalies appear to link to a rising trend and periods in earthquakes' power time series. This finding sheds new light on the mechanisms controlling the most destructive natural hazard.

A contemporary technique for calculating seismic risk is earthquake nowcasting (EN), which analyzes the progression of the earthquake (EQ) cycle in fault systems. 'Natural time' is a novel idea of time that serves as the foundation for EN assessment. The earthquake potential score (EPS), which has been discovered to have useful uses regionally and worldwide, is a unique tool EN uses to predict seismic risk. For the estimation of the EPS for the occurrences with the highest magnitude among these applications, we have since 2021 concentrated on Greece territory, applying sophisticated Artificial Intelligence (AI) algorithms, both wise (semi)supervised and unsupervised models, along with a customized dynamic sliding window technique that performs as a stochastic filter able to fine-tune the geo seismic occurrences. Long short-term memory (LSTM) neural networks, random forests, and clustering (geospatial) models are three machine learning techniques that are particularly good at finding patterns in vast databases and may be used to enhance earthquake prediction performance. In this study, we attempt to forecast whether practical Machine-learning and AI/Game-theoretic-based approaches can help predict big earthquakes and the normal future seismic cycle for 6-12 months. Specifically, we focus on answering two questions for a given region: (1) Is there a chance that a significant earthquake—say, one with a magnitude of M ≥ 6.0 will happen in the upcoming year? (2) What is the largest earthquake magnitude predicted in the upcoming year, and with which exact geographic coordinates (GCS)? Our results are quite promising and project a high precision accuracy score (≥ 98%) for seismic nowcasting in terms of four predictive parameters: the approximate (a) latitude, (b) longitude, (c) focal depth, and (d) magnitude of the phenomena.

Despite the fact that SMA restrainers exhibit a superelastic strain capacity of 7%, this capacity appears inadequate for isolated bridges due to the typically greater than 20cm relative dis-placements between girders during intense seismic events. In order to perform such a stroke, a SMA restrainer of greater than 3 metres in length might be required. In order to reduce the length of restrainers, a novel honeycomb damper constructed from superelastic shape memory alloy (SMA) is proposed. The proposed device, denoted as the superelastic SMA honeycomb damper (SHD), is comprised of steel plates to prevent the SMA plane from collapsing and superelastic SMA honeycomb to provide self-centering capability. By incorporating the large strain capacity of SMA and the geometrically nonlinear deformation of honeycomb structures, SHD has been developed to satisfy the requirements of bridge restrainers with large strokes. It is capable of functioning as a restrainer and energy dissipation device when subjected to dynamic tension and compression loads. The SHD was initially investigated from a theoretical perspective. Following this, a mul-ti-cell SHD specimen was manufactured. The specimen underwent axial tensile and compressive experiments in order to examine the mechanical properties of SHDs. Finally, experimental results were investigated through numerical simulation analyses of the SHDs using a three-dimensional high-fidelity finite element model. Additionally, a method for enhancing SHD was proposed. The findings indicate that SHD is capable of exhibiting superior self-centering capability and sta-ble hysteretic responses when subjected to earthquakes.

In recent decades, low-yielding seismic devices based on the use of friction dampers have emerged as an excellent solution for the development of building structures with improved reparability and resilience. Achieving an optimal design for such low-yielding seismic devices requires precise control of bolt preloading levels and predictability of the friction coefficient (CoF) between the damper interfaces. While various types of friction devices exist, capable of providing significant energy dissipation, ongoing research is focused on the development of novel friction materials that exhibit a stable hysteretic response, high CoF values, minimal differences between static and dynamic CoF, and predictable slip resistance. In this context, an experimental campaign was conducted at the STRENGTH Laboratory of the University of Salerno to evaluate the behaviour of new friction shims employing specially developed metal alloys. Specifically, the influence of the characteristics of the contact surfaces in the sliding area on the behaviour and performance of the friction device was analysed. The tests followed the loading protocol recommended by EN12159 for seismic device qualification. Monitored parameters included preloading force values and the evolution of slip resistance. The friction value was determined, along with its degradation over time. Finally, the material's performance in terms of hysteretic behaviour was assessed, providing a comparison of the tested specimens in terms of slip force degradation and energy dissipation capacity.

(1) Background: The intermediate-depth seismicity in the Vrancea region (Romania) is characterized by localized and persistent earthquake activity that culminates about two or three times in a century with the occurrence of a large event (M 6.5). Here we have revisited some important seismicity characteristics, using earthquake catalog data spanning two different time periods: 2005 – 2013 and 1960 – 2000. (2) Methods: we have determined the b-value of the frequency-magnitude distribution of earthquakes, using a maximum likelihood procedure, and estimated the parameter to quantify anomalous seismicity rate decreases and increases. (3) Results: by using data from the first period, we have confirmed the existence of a decreased b-value in the deepest part of the seismogenic zone; by using data from the second period, we have statistically confirmed the seismic quiescence that preceded the occurrence of the 1977 M7.4 Vrancea earthquake. (4) Conclusions: the decreased b-value has been interpreted either in terms of an increased lithostatic stress with depth or as an indicator of the depth range where the next major Vrancea earthquake may occur. The time variation of the seismicity parameter may reveal anomalous seismic quiescence and increased earthquake rates that may precede the occurrence of large earthquakes.

While the container crane is an important part of daily port operations, it has received little attention compared with other infrastructures, such as buildings and bridges. Crane collapse due to earthquake affects the operation of the port, and indirectly impacts the economy. This study proposes fragility analyses for various damage levels of the container crane that allow the port owner and partners to better understand the seismic vulnerability presented by container cranes. A large quantity of nonlinear time history analyses was applied for a three-dimensional (3D) finite element model to quantify the vulnerability of the container crane in considering the uplift and derailment behavior. The uncertainty of demand and capacity of the crane structures were also considered through random variables, i.e. elastic modulus of members, ground motion profile, and intensity. The results analyzed in the case of a Korean container crane showed that the probability of exceeding the first uplift with or without derailment is shown before the crane reaches the structure’s limit states. This means that under low seismic excitation, the crane might be derailed without any structural damage. But when the crane reaches the minor damage state, it is always coupled with a certain probability of uplift with or without derailment. This study also proposes the fragility curves developed for different structural periods to enable port stakeholders to assess the risk of their container crane.

The present study investigates the role of a simple inerter in supplemental devices for possible implementation in the matured seismic base isolation technique. Firstly, the response of the base-isolated structure with an optimally tuned mass damper-inerter (TMDI) is investigated to see the tuning effects. The time required to tune the TMDI was found to be significantly longer than the duration of a strong-motion earthquake. There was still a reduction in the response of the isolated structure, which is primarily due to the added damping and stiffness (ADAS) of TMDI and not because of the tuning effects. Hence, it is proposed that the corresponding ADAS of the TMDI be directly added to the isolation device. Secondly, the response of the base-isolated structures with the fluid inerter damper (FID) is studied. It was observed that the inerter of the FID does not influence the displacement variance of an isolated structure under broadband earthquake excitation. It implies that the response of the isolated structure with FID is primarily controlled by its counterpart fluid damper (FD). The performance of optimal TMDI, ADAS, FID, and FD to mitigate the seismic response of the flexible multi-story base-isolated structure under real earthquake excitations is also investigated. In terms of suppressing the displacement and acceleration responses of the isolated structure, it has been found that TMDI and ADAS perform similarly. Comparing the response of the isolated structure with FID and FD demonstrated that the inerter in the FID has detrimental effects on the isolated structures, in which the top floor's acceleration and base shear are substantially increased.

In general, the stone pagoda structures with discontinuous surfaces are vulnerable to lateral forces and are severely damaged by earthquakes. After the Gyeongju earthquake in 2016 and the Pohang earthquake in 2017, the earthquakes damaged numerous stone pagoda structures due to slippage, rotation and the separation of stacked stone. To evaluate seismic resistance of masonry stone pagoda structure, we analyzed the seismic behavior of stone pagoda structure using shaking table test. Shaking frequency, permanent displacement, maximum acceleration, rocking, and sliding were assessed. Responses to simulations of the Bingol, Gyeongju, and Pohang earthquakes based on Korean seismic design standard (KDS 41 17 00) were analyzed for return periods of 1,000 and 2,400 years. We found that the type of stylobate affected the seismic resistance of stone pagoda structure. When the stylobates were stiff, seismic energy was transferred from lower to upper regions of the stone pagoda, which mainly resulted in deformation of the upper region. When the stylobates were weak, earthquake energy was absorbed in the lower regions; this was associated with large stylobate deformations. The lower part of tower body was mainly affected by rocking, because the structural members were slender. The higher part of the stone pagoda was mainly affected by sliding, because the load and contact area decreased with height.

In this paper, optimum parameters of Tuned Mass Dampers (TMD) are considered to control the responses of 10-story shear building under harmonic loading and 22 set of seismic records of FEMA-P695. The criterion used to obtain the optimum parameters is to select mass ratio, the frequency (tuning) and damping ratio that would result in smallest lateral displacements. State-space equations of motion are presented to compute the structural responses by developing a MATLAB file. A 10-story shear building is presented as a case study to assess the effects of TMDs on the multi-story structures. The results indicate that using TMD can reduce structural responses up to the average 20% under earthquake excitation and up to 90% under harmonic loadings. TMDs are not always effective under any type of ground motion; therefore, being aware of the given location is significant to design TMDs properly.

Extraction of high-resolution surface waves is essential in surface-wave survey. Because reflections usually interfere with surface waves on X component in a multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. The situation goes more serious when the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between reflections and surface waves. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections respectively. Then, the sparse representation problem based on the morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extracting accurate dispersion curves.

Most European cities are characterized by very large areas, often formed by buildings with low quality, from a series of point of view. The possibility of renovating them is strategic to improve both the quality of life and to the possibility of economic recovery for building companies. In the last decades, the attention of the scientific community has been addressed to the energy renovation, thanks to the strong activities of the European Community in this field. However, since a relevant part of the EC territory is at risk of earthquake, the possibility to combine both energy and seismic renovation actions may be strategic for many countries. In particular, Italy and Romania are linked by a common social tradition that springs from the Roman Empire. Nowadays, this link is stronger, thanks to common interests in social, cultural and business fields. Therefore, the investigation of possible synergies for seismic and energy renovation strategies may be really interesting for both countries. This paper represents the first step in this direction. After an overview of regulations and common practices for buildings with reinforced concrete structures, in both states, some key combined renovation interventions will be described and discussed, as well as advantages and perspectives of integrated renovation approaches.

This paper presents the experimental and numerical study on a ductile beam-column connection between a composite reinforced concrete truss (CRCT) beam and Concrete Filled Tube (CFT) column subjected to bending and shear loads. Two experimental models with different beam-column joint testing schemes, extracted from the same prototype three-dimensional structure designed according to the rules of the capacity design provided by seismic code, were subjected to quasi-static cyclic tests by applying gravitational loads and the horizontal seismic force. The main objective of this paper is to verify the experimental ductile behavior of both specimens and to simulate the experimental global and local response by nonlinear static analysis considering different modelling approaches. The comparison between the experimental and numerical results highlights, for both models considered, the ductile and dissipative capacity of the connection system, designed following the criterion of the hierarchy of resistances proposed by the current Italian code. Different experimental setup showed similar results demonstrating the repeatability of the test and its reproducibility through the nonlinear numerical analysis.

The paper highlights the performance of the seismic isolation devices, installed on retrofitted buildings in reducing the seismic response when subjected to earthquakes. Two buildings from the beginning of the XX-th century in Bucharest are chosen from many more, monitored over the city area. We discuss the response of these base-seismic isolated structures, relying on good quality data acquired from the recent strong earthquake (03.11.2022, MW = 5.0). Elastic response spectra computed from recordings at two levels of each structure are used, placed under and right above the isolating layer. At one building the existence of previous recordings and the particularity of the sensors allow a comparison with other two relatively recent medium intensity earthquakes. The assessment is carried out in terms of maximum acceleration amax, measured at certain levels in each structure, spectral acceleration amplitude SAmax and spectral-peak corresponding period. We find that the base-isolation methodology is effective in reducing the response of the building right above the isolating layer, an observation valid for both structures, all components of the recordings, and spectral acceleration values. Moreover, the outcomes from the modal evaluation performed prior to rehabilitation and seismic isolation process are presented, by pointing out a higher newly acquired fundamental period of the isolated structures.

Non-compliant (NC) structures are often encountered in building construction in developing countries. This is a condition whereby erected buildings do not follow regulatory standards, especially in the provision of reinforcements. Therefore, under an earthquake load, the structures do not have sufficient resistance against such load. The structural elements of the building, which often have NC conditions, are the beam-column joints because they do not contain adequate shear reinforcements due to installation difficulty. This study aims to determine the structural performance of the reinforced concrete (RC) frame, which has a reinforcement deficiency in the beam-column joints. Numerical simulation was conducted on the Kakaletsis structure model by modifying the reinforcement details at the joints to represent the NC conditions. The non-linear modeling and analysis of the structural model were carried out using ATENA software. The analysis showed that the reduction in shear reinforcements in the NC model joint caused a decrease in load-carrying capacity by about 26.04%. A shift was also observed in the collapse pattern, i.e., from the beam to the end of the column, causing global failure and reducing the undamaged but increasing more severely damaged condition. This showed that the NC structure, due to the non-conformance of reinforcement, significantly reduced the structure's performance.

This study introduces a new procedure for three-component spectral matching of seismic ground acceleration records. The procedure involves preserving the phase angle and varying the Fourier amplitudes to match the spectra of the recorded records with a provided target spectrum that represents the spectral values of ground motions in three orthogonal directions. Several three-component recorded records were matched against two target response spectra to test the method. An accurate convergence was achieved in the velocity and displacement records. In addition, the scales among the components’ magnitude were maintained, creating realistic three-component ground motions. Such ground motion inputs are important to qualify critical structures sensitive to three-component motions. Our proposed procedure is novel because the present practices are mostly created based on one-component ground motions.

Understanding and improving seismic resilience in regions prone to earthquakes is crucial for mitigating the effects of natural disasters. This study zeroes in on Montenegro, a region frequently affected by seismic activity, with the goals of critically evaluating current resilience levels, pinpointing key preparedness gaps, and assessing the efficacy of existing response strategies. Employing qualitative methods, the research involved semi-structured interviews with residents from Montenegro's most vulnerable areas, including Nikšić, Podgorica, Bar, Kotor, Cetinje, Budva, Herceg Novi, and Berane. These participants, selected for their firsthand experiences with significant earthquake impacts, contributed to a deeper understanding through discussions that aligned with a broad conceptual framework, exploring everything from the nuances of citi-zen resilience to local government responses and personal preparedness. The study aimed to gather in-depth views on community resilience during earthquakes, evaluate citizens' knowledge and preparedness for such disasters, and examine local governance strategies for enhancing seismic resilience. It revealed varying resilience levels across communities, with some displaying well-structured strategies while others showed notable deficiencies. The findings underscore the urgent need for community-specific preparedness programs and improvements in both structural and educational frameworks to enhance resilience. This research highlights the necessity of a comprehensive approach that includes detailed risk assessments, tailored preparedness training, and stronger public awareness efforts. Additionally, it emphasizes strengthening local governments' capabilities to enact and sustain effective response measures to ensure ongoing community resilience against future seismic challenges.

In this study, three new demountable joints consisting of reinforced concrete columns and steel beams were proposed and their seismic performance was investigated using cyclic loading tests. The test results demonstrated that the three demountable RCS joints had good seismic performance. Using the finite element software ABAQUS, the influence of parameters such as beam flange thickness, bolt strength, and connector steel strength on the seismic performance of each joint was analyzed, and the influence of different parameters on the seismic behavior of the joint was determined. The results also showed that the three demountable RCS joints were sensitive to changes in the thickness of the steel beam flange, while the connector steel strength and bolt type had little impact on the joint's capacity. Additionally, shear capacity calculation formulas for the joint core area provided by different codes and researchers were compared with test and finite element results. The results showed that the calculation results of the ASCE guidance method, the Nishiyama method, and the CECS 347-2013 method were higher than the test values, while the calculation results of the Para method were lower because it did not consider the contribution of the cylindrical steel plate to the shear capacity of the joint core area.

Confined masonry (CM) is a construction system which consists of masonry wall panels enclosed by vertical and horizontal reinforced concrete confining elements. The presence of these confining elements distinguishes CM from unreinforced masonry system and makes this technology suitable for construction of structures in regions subjected to intense seismic or wind actions. CM construction has been used in many countries and regions, and has performed well in past earthquakes. The purpose of the paper is to review past research studies related to the seismic in-plane and out-of-plane behaviour of CM structures. The authors have identified the key design and construction parameters which were considered in past research studies and have performed statistical analyses to establish their influence on the seismic performance of CM buildings. For the purpose of this study the authors have compiled databases of previous experimental studies on CM wall specimens which were used for statistical analyses. Finally, the paper discusses research gaps and needs for future research studies which would contribute to the understanding of seismic behaviour and failure mechanisms of CM walls.

Nepal is one of the most seismically active regions in the world, as highlighted by the recent devastating 2015, Mw7.8 Gorkha earthquake and a robust assessment of seismic hazard is paramount for the design of earthquake-resistant structures. In this study we present a new probabilistic seismic hazard assessment (PSHA) model for Nepal. We considered data and findings from recent scientific publications, which allowed us to develop a unified homogenized seismicity catalogue, propose alternative Seismic Source Characterization (SSC) models including up-to-date parameters of major thrust faults like Main Frontal Thrust – MFT and Main Boundary Thrust – MBT, while also considering existing SSC models and various hazard modelling strategies within a logic tree framework. The sensitivity analyses show the hazard levels are generally higher for SSC models integrating the major thrust faults, followed by homogenous volume sources and smoothed seismicity approach. The hazard maps covering entire Nepal is presented as well as the Uniform Hazard Spectra (UHS) for 5 selected locations (Kathmandu, Pokhara, Biratnagar, Nepalganj and Dipayal) at return periods of 475- and 2,475-years considering Vs,30=760 m/s. The results obtained are generally consistent with most recent studies. However, a notable variability in hazard levels and several discrepancies with respect to the Nepal Building Code NBC105: 2020 [1] and Global Hazard Model, GEM [2] are noted and possible causes are discussed.

The steel damper column is an energy-dissipating member that is suitable for reinforced concrete (RC) buildings, and those used for multistory housing in particular. However, the effectiveness of steel damper columns may be affected by the behavior of surrounding members, and this effect can be severe in the case of seismic sequences. This article investigates the nonlinear response of building models having an RC moment-resisting frame (MRF) with and without steel damper columns under seismic sequences. The applicability of the concept of the momentary energy input to the prediction of the peak response of RC MRFs with damper columns under seismic sequences is also investigated. The main findings of the study are summarized as follows. (1) The peak response of RC MRFs with damper columns subjected to sequential accelerations is similar to the peak response obtained considering only the mainshock, whereas the cumulative strain energy of RC MRFs accumulates more for sequential accelerations. (2) The steel damper column is effective in reducing the peak and cumulative responses of RC MRFs in the case of sequential seismic input. (3) The relation of the hysteretic dissipated energy during a half cycle of the structural response and the peak displacement of the first modal response can be properly evaluated using the simple model proposed in this study.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

With the Sendai Framework (2015-2030) and the Paris Agreement (2015), the UN has been promoting at a global level, the priority objectives to protect the life and well-being of people, these documents of global consensus have scheduled in several countries, an extensive list of actions of responsibilities and commitments to the environment, to address natural disasters among those of greatest impact earthquakes and floods and among earthquakes (seismic activity). The materialization of the disaster is a natural or human-induced event, it manifests itself in permanent changes in society and by its origin it is classified as natural, anthropogenic (anthropogenic) and mixed, creating a worldwide problematic situation of immediate reaction. The attention and alert in the scientific community have been adding efforts, but in a disorganized way, with limited human and material resources and with globalized strategies still to be improved. The literature review of disaster risk management due to seismic activity, from 2008 to 2023, allows us to have updated information to identify the factors and deepen them, with the understanding, comprehension, and multidisciplinary knowledge. The selected researches that mention the factors (elements) that influence risk management of natural disasters due to seismic activity (RMNDDSA) allow us to know the advances and spaces to approach them, which constitutes the motivation to study the twenty-four (24) factors present in this type of disasters. The selected research articles indicate important advances that associate disaster risk management (DRM) and communication technology (ICTs). The technological means mentioned are well received and accepted by society, capable of detecting and communicating in real time seismic activity worldwide, with the help of social mobile networks, technological platforms, Twitter, Facebook, and others.

To achieve rapid post-earthquake repair of self-centering ribbed floor flat beam frame structures, a ductile hybrid joint consisting of dog bone weakened energy dissipating steel bars connected to the upper and lower column sections through high-strength threads based on the damage control design concept is proposed. By moving the ductile energy dissipating zone out to the locally weakened section of the energy dissipating steel bars and the locally unbonded prestressed steel bars in the core area, the residual deformation was limited and the seismic performance was improved. Based on the working principle of hybrid joints, low cycle loading tests were conducted on two joint specimens to analyze the influence of lateral prestress on the seismic performance of the hybrid joints. Numerical modeling methods were used to compare the position of the energy-consuming steel bars in the composite layer and the friction performance of joints. The research results indicated that the hybrid joint had stable load-bearing, deformation, and energy dissipation capabilities, with damage primarily concentrated on the energy-consuming steel bars. Even at an inter-story displacement angle of 5.5%, the upper and lower column segments remained elastic. After unloading, the connection seam at the joint was closed, and the self-centering performance was good. When the inter-story displacement angle reached 5.5%, the lateral prestress increased from 150 kN to 250 kN, the ultimate bearing capacity of the joint increased by 16.3%, and the cumulative energy consumption increased by 30.0%. The influence of the friction coefficient of the joint surface on the structural performance was set at a threshold of 0.7. When it was less than the threshold, the ultimate bearing capacity and initial stiffness of the joint increased with an increase in the friction coefficient. After reaching the threshold, the increase in the ultimate bearing capacity of the joint slowed down, and the rate of stiffness degradation gradually accelerated. This joint had excellent seismic performance and can also achieve post-earthquake repair of structures.

This paper presents an innovative approach for improving the seismic protection of existing structures by introducing an additional dissipative structure (ADS). The seismic energy impacting the building can be dissipated through the contribution provided by the ADS, thereby reducing the need for the existing building to ensure its seismic capacity. This retrofitting technique is well-suited for structures facing architectural restrictions or challenging-to-update elements. It can help address foundation issues by applying loads to new external components. This paper describes the design of the ADS and proposes a displacement-based design procedure. The design process involves a non-linear static analysis and a simple procedure that must be iteratively repeated until the retrofitting target is achieved. This approach is simple and computationally efficient and can also be used for complex and irregular structures. Such structures are frequently encountered, and existing structures often exhibit unusual geometries and materials requiring extensive numerical modeling. The efficacy of the technique was evaluated using the case studiy of a school building located in central Italy. The results of numerical analyses indicated that owing to the ADS’s contribution, the seismic capacity of both buildings was enhanced, addressing the challenges associated with complex foundation interventions.

Seismic vulnerability assessment in urban areas would in principle require the detailed modeling of each single building and the implementation of complex numerical calculations. This procedure is clearly difficult to apply at urban scale where many buildings have to be considered and therefore it is essential to have simplified, but at the same time reliable, approaches to vulnerability assessment. Among the proposed strategies, one of the most interesting concerns the application of machine learning algorithms, able to classify buildings according to their vulnerability on the basis of training procedures applied to existing datasets. In this paper machine learning algorithms will be applied to a dataset which collects and catalogs the structural characteristics of a large number of buildings and reports the damage observed in L’Aquila territory during the intense seismic activity occurred in 2009. A combination of a trained neural network and a random forest algorithm allows to identify an opportune “a-posteriori” vulnerability score, deduced from the observed damage, which is compared to an “a-priori” vulnerability one, evaluated taking into account characteristic indexes for building’s typologies. By means of this comparison an inverse approach to seismic vulnerability assessment, which can be extended to different urban centers, is proposed.

Landslide is one of the most common geological disasters in China, which is characterized by suddenness and uncertainty, and it is difficult to realize accurate identification, early warning and forecasting of landslide disaster by conventional means. With the development of high-resolution remote sensing satellites and InSAR surface deformation monitoring technology, the traditional means of landslide monitoring data sources are limited, and there is a lack of effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors and other issues. In this paper, the area extending 10 km outside the VII isobar of the Gengma earthquake is taken as the study area, and 13 evaluation factors are screened out by integrating the factors of InSAR surface deformation, topography and geological environment, and the Bayesian Optimized Convolutional Neural Network (BO-CNN) is used for the evaluation of landslide susceptibility, and the BO-RF and PSO-SVM models are selected for the comparative analysis. The model accuracy evaluation was carried out by three indexes: ROC curve, AUC value and FR value, in which the ROC curves of PSO-SVM, BO-RF and BO-CNN were all close to the upper-left corner of the corner, and the AUC values were 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslide in the high susceptibility area of BO-CNN was as high as 14.9, and was higher than that of PSO-SVM and BO-RF, respectively. SVM and BO-RF model is 4.55 and 3.69 higher, the experimental results show that the BO-CNN model used in this paper has a better effect in landslide susceptibility evaluation, and the research results of the local government's disaster prevention and mitigation measures are of great significance.

The information of seismic damage of buildings in SAR images of different time phase, especially in SAR images after earthquake, is easily disturbed by other factors, which affects the accuracy of information discrimination. In order to identify and evaluate the distribution information of the seismic damage accurately and make full use of the abundant texture features in the SAR image. The conventional method of change detection based on texture features usually takes the pixel as the calculating unit. In this paper, a method of texture feature change detection of SAR images based on watershed segmentation algorithm is proposed. Based on the optimization of texture feature parameters, the feature parameters are segmented by the watershed segmentation algorithm, and the feature object image is obtained. This method introduces the idea of object oriented, and carries out the calculation of the difference map at the object level, Finally, the classification threshold value of different types of seismic damage types is selected, and the recognition of building damage is achieved. Taking the ALOS data before and after the earthquake in Yushu as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%, Compared with pixel-based methods, it is proved that the proposed method is effective.

Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to landscapes, infrastructure, and human life. Triggered by factors such as intense precipitation, seismic activities, or volcanic eruptions, these events can cause extensive damage and endanger nearby communities. A comprehensive understanding of landslide characteristics, including spatio-temporal patterns, dimensions, and morphology, is vital for effective landslide-disaster management. Existing Remote Sensing approaches mostly use either optical or Synthetic Aperture Radar (SAR) sensors. Integrating information from both these types of sensors promises greater accuracy for identifying and locating landslides. This study proposes a novel approach, the ML-LaDeCORsat (Machine Learning-based coseismic Landslide Detection using Combined Optical and Radar Satellite Imagery), that integrates freely available Sentinel-1, Palsar-2, and Sentinel-2 imagery data, along with relevant spectral indices and suitable bands using machine-learning-based classification for coseismic landslide detection implemented in Google Earth Engine (GEE). The approach includes a robust and reproducible training and validation strategy. Using landslides from four different earthquake case studies, we demonstrate the superiority of our approach over existing solutions in coseismic landslide iden-tification and localization, providing a detection accuracy of 87-92%. ML-LaDeCORsat can be adapted to other landslide events (GEE script is provided). Transfer learning experiments proofed that our model can be applied to other coseismic landslide events without the need for additional training data. Our novel approach therefore facilitates quick and reliable identification of co-seismic landslides, highlighting its potential to contribute towards more effective disaster management.

A quite energetic seismic excitation consisting of one main and additional three distinctive earthquake clusters that occurred in the transition area between the Kefalonia Transform Fault Zone (KTFZ) and the continental collision between Adriatic and Aegean microplates, is thoroughly studied after high–precision aftershocks’ relocation. The activated fault segments are in an area where historical and instrumental data have never claimed the occurrence of a catastrophic (M>6.0) earthquake. The relocated seismicity initially defines an activated structure extending from the northern segment of the Lefkada branch of KTFZ with the same NNE–SSW orientation and dextral strike-slip faulting and then keeping the same sense of motion its strike becomes NE–SW and its dip direction NW. This provides unprecedented information on the link between the KTFZ and the Collision front and sheds more light on the regional geodynamics. The earthquake catalog, which is specially compiled for this study, starts one year before the occurrence of the Mw5.4 mainshock and adequately provides the proper data source for investigating the temporal variation of the b–value, which might be used for discriminating foreshock and aftershock behavior.

This study presents an exploration into identifying the interactions between ocean waves and the continental margin in the origination of double-frequency (DF, 0.1-0.5 Hz) microseisms recorded at 33 stations across East Coast of USA (ECUSA) during a ten-day period of ordinary ocean wave climate. Daily primary vibration directions are calculated in three frequency bands and projected as great circles passing through each station. In each band, the great circles from all stations exhibit largest spatial density primarily near the continental slope in the western North Atlantic Ocean. Generation mechanisms of three DF microseism events are explored by comparing temporal and spatial variations of the DF microseisms with the migration patterns of ocean wave fronts in Wavewatch III hindcasts. Correlation analyses are conducted by comparing the frequency compositions of and calculating the correlation coefficients between the DF microseisms and the ocean waves recorded at selected buoys. The observations and analyses lead to a hypothesis that the continental slope causes wave reflection, generating low frequency DF energy and that the continental shelf is where high frequency DF energy is mainly generated in ECUSA. The hypothesis is supported by the primary vibration directions being mainly perpendicular to the strike of the continental slope.

Research shows that in earthquakes the ground response changes in areas where there are underground cavities. Due to the fact that subways and underground tunnels pass from beneath buildings in urban areas, these changes in ground response have a direct impact on the seismic behavior of structures. In this study, first by model validity and reliability of the results, steel structures modeling was conducted and steel structure behavior was evaluated due to Tunnel-Soil-Structure seismic interaction. Parameters studied are number of stories, soil type, tunnel depth, horizontal tunnel-structural distance and dynamic loading. Considering that one of the most important parameters of structural control is drift and story displacement, so this important factor will be considered. The results show that tunneling has a direct effect on the rate of structural displacement and increases the structural response. Also, the behavior of the structure is affected by the position of the structure at the ground level and the position of the tunnel and this should be considered during the design phase of the structures.

This study develops a wavelet maxima-based methodology to extract anomalous signals from microwave brightness temperature (MBT) observations for seismic estimation. MBT, acquired via satellite microwave radiometry, enables subsurface characterization penetrating clouds. Five earthquake categories were defined contingent on locale (oceanic/terrestrial) and ambient traits (soil hydration, vegetal covering). Continuous wavelet transform was applied to preprocess annualized MBT readings preceding and succeeding prototypical events of each grouping, utilizing optimized wavelet functions and orders tailored to individualized contexts. Wavelet maxima graphs visually portraying signal intensity variations facilitated identification of aberrant phenomena, including pre-seismic accrual, co-seismic perturbation, and postsismic remission signatures. Casework found 10GHz horizontal-polarized MBT optimally detected signals for aquatic and predominantly humid/vegetative settings, whereas 36GHz horizontal-polarized performed best for arid, vegetated landmasses. This preliminary investigation establishes an analytical framework, albeit reliant on qualitative appraisals. Quantitative machine learning methods are warranted to statistically define selection standards and augment empirical forecasting leveraging lithospheric stress state inferences from sensitive MBT parametrization.

The unreliable prediction of the low frequency components from inverted acoustic impedance causes uncertainty in quantitative seismic interpretation. To address this issue, we first calculate various seismic and geological attributes that contain low frequency information, such as relative geological age, interval velocity, and integrated instantaneous amplitude. Then, we develop a method to predict the low frequency content of seismic data using these attributes, their high frequency components, and recurrent neural networks. Next, we test how to predict the low frequency components using stacking velocity obtained from velocity analysis. Using all the attributes and seismic data, we propose a supervised deep learning method to predict the low frequency components of the inverted acoustic impedance. The results obtained in both synthetic and real data cases show that the proposed method can improve the prediction accuracy of the low frequency components of the inverted acoustic impedance, with the best improvement in a real data example of 57.7% compared with the impedance predicted using well log interpolation.

Fractures are present in hydrocarbon reservoirs of different porosity ranges. Seismic anisotropy has been widely used in fracture characterization and shown to be sensitive to background matrix porosities in theoretical studies. An understanding of the effects of background porosity on seismic anisotropy could improve seismic characterization in different fractured reservoirs. Based on synthetic rocks with controlled fractures, we conducted laboratory experiments to investigate the influence background porosity has on P wave anisotropy and shear wave splitting. A set of rocks containing the same fracture density (0.06) with varying porosities of 15.3%, 22.1%, and 30.8% were constructed. P and S wave velocities were measured at 0.5 MHz as rocks were water saturated. Results show that when porosity increased from 15.3% to 22.1%, P wave anisotropy and shear wave splitting exhibit slight fluctuations. However, when porosity continued to increase to 30.8%, P wave anisotropy declined sharply while shear wave splitting stayed nearly constant. The measured results were compared with predictions from equivalent medium theories. Qualitative agreements were found between theoretical predictions and measured results. In Eshelby-Cheng model, the increase of porosity reduces the fracture-induced perturbation in the fracture normal direction, resulting in a lower P wave anisotropy. In Gurevich(2003) model, the increase of porosity can reduce the compressional stiffness in parallel direction to a larger extent than that in perpendicular direction, thus leading to lower P wave anisotropy.

This paper is intended at highlighting the main mechanical parameters controlling the behavior of the so-called "acceleration-sensitive" Non-Structural Components (NSCs). In the first part a short review of the current state of knowledge and the critical issues related to the prediction of the seismic response of NSCs is reported. Then, the paper presents the results of a numerical parametric analysis intended to capture the key features of the dynamic response of a two-degree-of-freedom (2DOF) system which is supposed to be representative of both the main structure and the "non-structural" component (NSC). Particularly, it allows to simulate the coupled behaviour of both main structure and NSC and evaluating their response. The main parameters controlling the dynamic response of NSCs emerge from this study, which could pave the way towards formulating more mechanically consistent relationships for evaluating the maximum accelerations induced by seismic shakings on NSCs.

A new lateral force-resisting wall panel is presented for applications in mid-rise prefabricated lightweight steel construction in seismic prone regions. This panelised system is composed of a hot-rolled frame and cold-formed studs and tracks, which works as a lateral force resisting system in lightweight steel framing. The proposed hybrid panel system exhibits proper ductility and energy dissipation behaviour. The hysteretic responses of full-scale panel experiments demonstrate that the system can safely resist high cyclic loads. The hot-rolled steel part, on the other hand, can significantly improve the initial lateral stiffness of the total system that will control the maximum allowable drift of multi-story buildings. Finally, in a case study, by applying the proposed system to the design of a mid-rise building in a high seismic area, the performance of the hybrid panels, are compared with those of fully hot-rolled systems (moment resisting frames) and fully cold formed systems. The findings indicate that applying hybrid panels will result in lower weights and better performance in seismic prone regions.

Natural events such as floods, fires, tsunamis, earthquakes and others have nowadays caused serious damage to human beings and nature. The precise detection of these natural events and especially the earthquake has nowadays become the focus of many computer and geoscientific researchers. Computer science and machine learning algorithms have revolutionized early detection and prediction of these events. Hence, a fuzzy method has been initially used in this article to enhance the authenticity of data based on application of effective variables and then combination of neural network algorithms of the MLP perceptron and radial network of RBF in form of a collective learning system in order to more accurately identify seismic events on a small scale. It was observed after simulating the proposed method that the proposed method has significantly improved based on actual error and root-mean-square error (RMSE) criteria compared to basic methods.

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation

The size of the population and the need for residential spaces are increasing. One possible solution is to add new floors to existing buildings. The positive aspects of such a solution with respect to its socio-economic impact and impact on the environment is that large amounts of carbon dioxide release will be avoided, waste and its treatment will be reduced, and agricultural land and green spaces will be preserved. However, adding floors to existing structures might be structurally challenging, especially in terms of the behavior under seismic actions. This paper presents a numerical study of a reinforced concrete frame in an old building to which new floors are subsequently added. The analysis shows that the frame does not behave as a whole with the old part of the structure, nor does it behave the same as if it were made with rigid joints compared to additional ones connected using hinge joints. The change from the corner (knee) joint to the external joint has its own effect on the distribution of internal forces in the structure as a whole and in the joint in particular.

The probability distribution of the interevent time between two successive earthquakes has been subject of numerous studies due to its key role in seismic hazard assessment. In recent decades, many distributions have been considered and there has been a long debate about the possible universality of the shape of this distribution when the interevent times are suitably rescaled. In this work we aim to find out if there is a link between the different phases of a seismic cycle and the variations in the distribution that best fits the interevent times. To do this, we consider the seismic activity related to the Mw 6.1 L’Aquila earthquake that occurred on April 6, 2009 in central Italy by analyzing the sequence of events recorded from April 2005 to July 2009, and then the seismic activity linked to the sequence of the Amatrice-Norcia earthquakes of Mw 6 and 6.5 respectively and recorded in the period from January 2009 to June 2018. We take into account some of the most studied distributions in the literature: q-exponential, q-generalized gamma, gamma and exponential distributions and, according to the Bayesian paradigm, we compare the value of their posterior marginal likelihood in shifting time windows with a fixed number of data. The results suggest that the distribution providing the best performance changes over time and its variations may be associated with different phases of the seismic crisis.

Advanced machine learning algorithms, have the potential to be successfully applied to many areas of system modelling. In the present study the capability of ten machine learning algorithms in predicting the structural damage of an 8-storey reinforced concrete frame building subjected to single and successive ground motions is examined. From this point of view, the initial damage state of the structural system, as well as 16 well known ground motion intensity measures are adopted as the features of the machine-learning algorithms that aim to predict the structural damage after each seismic event. The structural analyses are performed considering both real and artificial mainshock–aftershock sequences, while the structural damage is expressed in terms of two overall damage indices. The comparative study results in the most efficient damage index, as well as the most promising machine learning algorithm in predicting the structural response of a reinforced concrete building under single or multiple seismic events. Finally, the configured methodology deployed in a user-friendly web-application.

In the context of seismic risk, studying the characteristics of urban soils and of the built environment means adopting a holistic vision of the city taking a step forward compared to the current microzonation approach. Based on this principle, CLARA WebGIS aims to collect, organise, and disseminate the available information on soils and buildings in the urban area of Matera. The geodatabase is populated with i) 488 downloadable geological, geotechnical, geophysical, surveys; ii) geological, geomorphological, and seismic homogeneous microzones maps and iii) a new Digital Surface Model. The CLARA WebGIS (https://smartcities-matera-clara.imaa.cnr.it/) is the first publicly available database reporting for the whole urban area the spatial distribution of the fundamental frequencies for soils and the overlying 4043 buildings, along with probability levels of soil-building resonance. The WebGIS is addressed to a broad target of end users (local government, engineers, and geologists, etc.) as a support to the implementation of seismic risk mitigation strategies in terms of urban planning, seismic retrofitting, and management of post-earthquake crises. We recommend that the database be managed by local administrators, who would also have the task of deciding on future developments and continuous updating as new data becomes available.

Eight samples of limestones and marbles were studied by neutron diffraction to collect 2 Quantitative Texture (i.e., Crystallographic Preferred Orientations or CPO) of calcite deforming at 3 different depths in the crust. We studied the different Texture patterns developed in shear zones at 4 different depth and their influence on seismic anisotropies. Samples were collected in the French and 5 Italian Alps, Apennines, and Paleozoic Sardinian basement. They are characterized by isotropic to 6 highly anisotropic (e.g., mylonite shear zone) fabrics. Mylonite limestones occur as shear zone horizons 7 within the Cenozoic Southern Domain in Alpine thrust-and-fold belts (Italy), the Briançonnais domain 8 of the Western Alps (Italy-France border), the Sardinian Paleozoic back-thrusts or in the Austroalpine 9 intermediate units. The analyzed marbles were collected in the Carrara Marble, in the Austroalpine Units 10 in the Central (Mortirolo) and Western Alps (Valpelline). The temperature and depth of development of fabrics vary from < 100◦C, to 800◦C and depth from <10 km to about 30 km, corresponding from upper 12 to lower crust conditions. Quantitative Texture Analysis shows different types of patterns for calcite: 13 random to strongly textured. Textured types may be further separated in orthorhombic and monoclinic 14 (Types A and B), based on the angle defined with the mesoscopic fabrics. Seismic anisotropies were 15 calculated by homogenizing the single crystal elastic tensor, using the Orientation Distribution Function 16 calculated by the Quantitative Texture Analysis. The resulting P- and S-waves anisotropies show a wide 17 variability due to the textural types, temperature and pressure conditions, and dip of the shear planes.

In this study, we define screening maps for Italy that classify sites based on their potential for triggering landslides. To this end, we analyze seismic hazard maps and hazard disaggregation results on a national scale considering four spectral periods (0.01s, 0.2s, 0.5s, and 1.0s) and three return periods (475, 975, and 2475 years). First, joint distributions of magnitude (M) and distance (R) from hazard disaggregation are analyzed by means of an innovative approach based on image processing techniques to find all modal scenarios contributing to the hazard. In order to obtain the M-R scenarios controlling the triggering of earthquake-induced landslides at any computation node, mean and modal M-R pairs are compared to empirical curves defining the M-R bounds associated with landslide triggering. Three types of landslides are considered (i.e., disrupted slides and falls, coherent slides, and lateral spreads and flows). As a result, screening maps for all of Italy showing the potential for triggering landslides based on the level of seismic hazard are obtained. The maps and the related data are freely accessible at the following web address: https://distav.unige.it/rsni/slideq.php.

The use of friction-based Beam-to-Column Connections (BCC)s for earthquake-resistant Moment Resistant Frames (MRFs), aiming at eliminating damage to beam end sections due to the development of plastic hinges, has taken hold since the early eighties. Different technical solutions were proposed for steel structures, some were also designed for timber structures, while few more recent studies concern friction joints employed in reinforced concrete structures. Research aimed at characterizing the behavior of joints has focused on the evaluation of the tribological properties of the friction materials, coefficient of friction, shape and stability of the hysteresis cycles, influence of the temperature, speed of load application, effects of the application method, stability of preload, the influence of seismic excitation characteristics on the structural response, statistical characterization of amplitude and frequency of the slip excursion during seismic excitation. Studies aimed at identifying the design parameters capable of optimizing performance have focused attention mainly on the slip threshold, device stiffness, and deformation capacity. This review compiles the main and most recent solutions developed for MRFs. Furthermore, the pros and cons for each solution are highlighted, focusing on the dissipative capacity, shape and stability of hysteresis loops. In addition, the common issues affecting all friction connections, namely characteristics of friction shims and the role of bolt preload, are discussed. Based on the above considerations, a guideline can be outlined, which can help to choose the appropriate solutions for beam-to-column connections for MRFs.

In recent years, the use of long-term seismic monitoring systems for the protection of structures is becoming increasingly widespread. This is because more and more awareness is gradually developing regarding the importance of keeping structures under observation so as to prevent any damage scenarios. Within the field of Structural Health Monitoring, data driven techniques allow to process and analyze data collected on site. This paper presents a Mode Tracking procedure to obtain the time-histories of the natural frequencies of a monumental structure. The procedure is applied on the Sanctuary of Vicoforte, an important monumental structure site in Piedmont known for its imposing oval dome and characterized by a permanent structural monitoring system. Through the procedure presented in the paper it has been possible to obtain and observe the time series of the first natural frequencies of the structure considering various aspects, including the temperature variation.

Expanded polystyrene (EPS)- block geofoam is an extremely lightweight fill material utilized in many geotechnical applications such as roadway and railway embankments. This study provides a methodology for analyzing the load-bearing capacity and horizontal sliding failure mechanisms for seismic internal stability analysis of EPSblock geofoam embankments. The seismic analysis procedure is demonstrated by analysis of one of the EPS-block geofoam embankments that Tennessee Department of Transportation is proposing a partial replacement of an existing bridge in Memphis, Tennessee in the USA. The objective of the seismic analysis procedure is to determine stresses from anticipated earthquakes to select the proper type of EPS considering both the 1% and 2% strain criteria that can support the anticipated increase in stress and potential horizontal displacements due to dynamic and static stresses. The study revealed that the 2% criterion provides an economical advantage compared to the 1% criterion.

Direct sizing criteria represent useful tools in the design of dissipative bracing systems for the advanced seismic protection of existing frame structures, especially when incorporated dampers feature a markedly non-linear behaviour. An energy-based procedure is proposed herein to this aim, focusing attention on systems including fluid viscous devices. The procedure starts by assuming prefixed reduction factors of the most critical response parameters in current conditions, which are evaluated by means of a conventional elastic finite element analysis. Simple formulas relating the reduction factors to the equivalent viscous damping ratio of the dissipaters, ξ_eq, are proposed. These formulas allow calculating the ξ_eq values that guarantee the achievement of target factors. Finally, the energy dissipation capacity of the devices is deduced from ξ_eq, finalizing their sizing process. A detailed description of the procedure is presented in the article, by distinguishing the cases where the prevailing structural deficiencies are represented by poor strength of the constituting members, from the cases having excessive horizontal displacements. A demonstrative application to the retrofit design of a reinforced concrete gym building is then offered to explicate the steps of the sizing criterion in practice, as well as to evaluate the enhancement of seismic response capacities generated by the installation of the dissipative system.

Abstract: The establishment of a circular economy in the mining sector, taking advantage of innovations in the exploration and development of hydrocarbon reserves, [ ], their [ ], transportation [ ] and subsequent processing [ ] are significant concerns. The issues surrounding the employment of technology targeted at enhancing environmental safety to increase the productivity of the reproduction process of the natural gas and oil resource base are equally important. The paper discusses the use of green seismic technology of survey to determine the oil and gas potential of the subsoil. A methodological toolkit is proposed for carrying out technical and economic calculations to determine indicators of the environmental and economic efficiency of using innovative resource-saving technology for geological survey in areas densely planted with forests. The purpose of the work is to establish the viability of employing resource-saving technology known as Green Seismic to search for promising hydrocarbon objects in forested areas and determine the expected environmental and economic benefits of geological exploration using the suggested enhanced methodology for their evaluation. The tasks set to achieve the goal were solved using methods of geological and economic assessment of the hydrocarbon raw material potential of territories and water areas, environmental assessment of the negative influence of anthropogenic environmental impact on the natural environment, economic and statistical methods of performing technical and economic calculations to determine performance indicators for the implementation of innovative projects in the field of geological exploration. The novelty of the results obtained lies in the proposed improved algorithm for conducting an environmental and economic assessment of geological exploration for hydrocarbon raw materials, a conceptual description of the Green Seismic technology, systematization of technical, economic, and environmental risks, justification of new regional directions for geological exploration using resource-saving seismic exploration technology.

Natural calamities observation, study and simulation has always been a prime concern for disaster management agencies. Billions of dollars are spent annually to explore geo-seismic movements especially earthquakes but it has always been a unique accident. The real-time study of seismic waves, ground motions, and earthquakes always needed a programmable mechanical structure capable of physically producing the identical geo-seismic motions with seismology domain definitions. A programmable multi-parametric five degrees of freedom electromechanical seismic wave events simulation platform to study and experiment seismic waves and earthquakes realization in the form of geo-mechanic ground motions is exhibited in this work. The proposed platform was programmed and interfaced through an IoT cloud-based Web application. The geo-mechanics was tested in the range of i) frequencies of extreme seismic waves from 0.1Hz to 178Hz; ii) terrestrial inclinations from -10.000° to 10.000°; iii) velocities of 1km/s to 25km/s iv) variable arrival times 1us to 3000ms; v) magnitudes M1.0 to M10.0 earthquake; vi) epi-central and hypo-central distances of 290+ and 350+ kilometers. Wadati and triangulation methods have been used for entire platform dynamics design and implementation as one of key contributions in this work. This platform is as an enabler for a variety of applications such as training self-balancing and calibrating seismic-resistant designs and structures in addition to studying and testing seismic detection devices as well as motion detection sensors. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems.

Various natural disasters such as floods, fires, earthquakes, etc. have affected human life. Detection and classification of large and small earthquakes caused by natural or abnormal events have been always important to Earth scientist. One of the most important research challenges in this field is the lack of an effective method for identifying and categorizing various types of seismic events at less important and important levels. Based on latest achievements of Data Mining international institutions such as Rexer-KDnugget-Gartner and also newest authentic articles, SVM, KNN, C4.5, MLP are from most important and popular and leading classifiers in data world.Therefor in present study, a boost learning system consisting support vector machine algorithms with linear regression, MLP Neural Network ، C4.5 decision tree and KNN near neighborhood have been utilized in a combined form to detect and categorize micro seismic events. In general, the steps involved in the proposed method are: 1) performing artificial seismic tests, 2) data gathering and analysis, 3) conducting preprocessing and separating training and testing samples, 4) generating relevant models with training samples and detecting and categorizing test samples and 5) extracting a cluster with the maximum candidate using boost learning. After simulations, it was observed that the accuracy of proposed boost method to the best answer was about 6.1% higher compare to other methods and the error rate was 0.082% of recalling. Accuracy of detection and classification to the best answer were also improved compare to other methods up to 2.31% and 6.34%, respectively.

Identifying ambient noise-based (ANb) signatures of streams can help in the estimation of their erosive potential (EP) that promotes reverie landslides and soil losses in the fluvial valleys. This is particularly imperative on flooding or rainy days, leading to stronger erosion-prone conditions (colluvium and boulders) of the valley beds inferred from georadar attribute analysis. Developing such research direction can benefit the local communities, as is the case with the Cerrado region of Brazil, where these phenomena have high destructive potential with social, economic, and climatic implications. For the present study, a seasonal stream in the Federal District of Brazil was investigated by ANb monitoring supported by Ground Penetration Radar (GPR) for site characterization. The ANb monitoring was conducted (at a safe distance) with a seismometer over several durations of dry and rainy conditions. The power spectral density (PSDs) was computed as a function of several variables, including weather conditions (rainfall, wind speed, and pressure), time-frequency spectrograms, and ambient noise displacement root mean square (RMS). This analysis also considered the single station horizontal-to-vertical spectral ratio (HVSR), where rain, wind, pressure, river flow and anthropogenic signatures were evident (at selective frequency ranges). Multi-peaks that emerged on the HVSR curve were further analyzed to identify amplitude and frequency changes, and the three peaks shift on average to a lower position during the rainy period. The GPR amplitude and waveform variation features were attributed to the stratigraphy (i.e., the boundary between valid and invalid regions and coherence value) of the floodplain and regions susceptible to erosion (erosion-prone lithological spots). This approach provides the basis for non-destructive monitoring tools enabling the detection of 'seismic signatures' and weak spots of the fluvial channels for improving environmental management.

The value of artificial intelligence and machine learning applications for use in heritage research is increasingly appreciated [1]. In specific areas, notably remote sensing, data sets have increased in extent and resolution to the point that manual interpretation is problematic and availability of skilled interpreters to undertake such work is limited. Interpretation of geophysical data sets associated with prehistoric submerged landscapes is particularly challenging. Following the last glacial, sea levels rose 120 metres globally, and vast, habitable landscapes were lost to the sea. These landscapes were inaccessible until extensive remote sensing data sets were provided by the offshore energy sector. In this paper, we provide results of a research programme centred on AI applications using data from the southern North Sea. Here, an area of c.188,000 km2 of habitable terrestrial land was inundated between c. 20,000 BP and 7,0000 BP, along with the cultural heritage it contained [2]. As part of this project, machine learning tools were applied to detect and interpret features of archaeological significance from shallow seismic data. The output provides a proof-of-concept model demonstrating verifiable results and the potential for further, more complex leveraging of AI interpretation for the study of submarine palaeolandscapes. Image: Adobe Firefly Generative AI using keywords - marsh landscape deep underwater, auroch skull half-buried in peat

With the rapid development of China's economy, construction industrialization has become the main development trend of China's construction industry, and the convenient, efficient, environmental protection has become the new fashion, therefore the application of prefabricated building is more and more common. Stair serves as the weak link in prefab type building, the connecting node has an important influence on its failure. In this paper, pseudo-static tests are carried out on the joints in different forms of ladder holes to study the mechanical properties of flexible hinge points filled with flexible materials, and the hysteresis curve, skeleton curve and bearing capacity of each specimen are analyzed. The test results show that the flexible hinge can give full play to its flexible characteristics to ease the stress of ladder beam, pin bolt reinforcement and ladder hole, and the bearing capacity of flexible hinge points is moderate, which can not only mitigate the inclined bracing effect under the action of small and medium earthquakes, but also ensure the stair does not fall off under the action of large earthquakes. Through the experiment comparison, the ladder hole adopts node form 2, which can give full play to the advantage of flexible material.

In this paper we describe the potentialities of a tool for the visualization of experimental results directly on a three-dimensional model. The case study concerns the visualization of the results of a dynamic finite element analysis (FEA/FEM) applied to the calculation of seismic risk on works belonging to the Italian infrastructural heritage, specifically bridges, viaducts and overpasses. The project is based on finite element analysis performed on an exemplary set of 8 structures located on the Italian territory, performed by means of the open-source software framework OpenSees, according to the guidelines indicated in the Technical Standards for Construction NTC08. The application created for this project is classifiable as a webGIS, since all data are georeferenced and visualized on a map through an application executed through a browser. The graphical interface displays the interested works on the map of the Italian territory and allows to select them by mouse click. Following the selection, a 3D rendering of the model of the work and the surrounding terrain is shown, in which the results of the analysis are represented using color gradients directly on the three-dimensional model. The necessary tools are present for the selection of the type of result and for the animation in real time of the response of the work to the seismic action. The 3D representation is freely navigable by the user thanks to intuitive tools of panning, rotation and zoom through mouse and keyboard. The application takes advantage of HTML5, CSS and Javascript to show graphical features such as Cartesian diagrams of accelerograms used in modal analysis.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It provides an image of the subsurface using the same principles as ultrasound medical imaging. It is based on emitting a sound (pressure) wave through the subsurface and recording the reflected echoes using hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors). Contrary to medical imaging, which is done in real time, subsurface seismic imaging is an offline process that involves a huge volume of data and needs considerable computing power. The raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = underfiltering, noise remaining in the data; optimal = good filtering; harsh = overfiltering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km2) to QC the results of the swell noise attenuation process in marine seismic data. The results are encouraging and helped identify localized issues that were difficult for a human to spot.

To quantify damage to reinforced concrete (RC) column members after an earthquake, an engineer needs to know the maximum applied force that was generated by the earthquake. Therefore, in this work, piezoceramic transducers are used to detect the applied force on an RC column member under dynamic loading. To investigate the use of post-embedded piezoceramic sensors in detecting the force that is applied to RC columns, eight full-size RC column specimens with various failure modes are tested under specific earthquake loadings. Post-embedded piezoceramic sensors are installed at a range of depths (70-80 mm) beneath the surface of a column specimen to examine the relationship between the signals that are obtained from them and the force applied by the dynamic actuator. The signals that are generated by the post-embedded piezoceramic sensors, which correlate with the applied force, are presented. These results indicate that the post-embedded piezoceramic sensors have great potential as tools for measuring the maximum applied force on an RC column in an earthquake. Restated, signals that are obtained from post-embedded piezoceramic sensors on an RC column in an earthquake can be used to determine the applied force and corresponding damage or residual seismic capacity.

Cable-supported façades represent a novel approach in the design and technology of double skin façades (DSF). This type of systems not only offer flexibility in terms of exterior finishes, but also regulates the access of solar radiation, thereby transforming the appearance of the building in response to varying daylight conditions. However, the structural performance of these façades under wind, impact and seismic loads remains an active area of research. The study is a groundbreaking work that experimentally evaluates the wind and seismic behaviour of these type of façades. The methodology used for the evaluation of flexible masonry facades includes laboratory tests analysing the individual capacity of the connections and materials of the system under standardized and non-standardized procedures. A full-scale experimental sub-assembly specimen of a representative module of the façade is also subjected to uniformly distributed pressures of wind load tests as well as hard body and soft body impact tests. The setup considered the border conditions, tension loads, and actual materials. Furthermore, the earthquake assessment includes tests of full-scale specimens subjected to these demands. Research findings allowed the refinement and redesign of the system's components granting the validation of the DSF used as a case study.

Recent scholarship highlights the significant environmental impact of the expanding hydraulic fracturing industry, necessitating up-to-date, comprehensive, national-scale assessments. Addressing this gap, this literature review provides a thorough analysis of the contamination and induced seismicity associated with shale-gas hydraulic fracturing in the United States. Employing systematic reviews of literature and federal reports up until July 2023, this study reveals multiple areas of concern. Notably, water and soil contamination, seismic activity, and air pollution are identified as significant challenges linked to shale gas extraction. However, ongoing studies are actively exploring remediation strategies, including advancements in monitoring and treatment technologies, aimed at mitigating the impact of contamination. These findings underscore the need for stringent regulations, continuous research, and effective management practices. This work emphasizes the importance of a collaborative approach that leverages field studies, experimental investigations, and computational advancements to ensure the responsible development of shale gas resources.

In this article we present a SCILAB implementation of algebraic iterative reconstruction methods for discretisation of inverse problems in imaging. These so-called row action methods rely on semi-convergence for achieving the necessary regularisation of the problem. We implement this method using SCILAB and provide a few simplified test problems: medical tomography, seismic tomography and walnut tomography.Numerical results show the capability of this method for the original and perturbed right-hand side vector.

Taking into consideration the seismic vulnerability of older buildings and the increasing need for reducing their carbon footprint and energy consumption, the application of an innovative system is investigated; the system is based on the use of textile reinforced mortars (TRM) and thermal insulation as a means of combined seismic and energy retrofitting of existing masonry walls. Medium scale tests were carried out on masonry walls subjected to out-of-plane cyclic loading. The following parameters were investigated experimentally: placement of the TRM in a sandwich form (over and under the insulation) or outside the insulation, one-sided or two-sided TRM jacketing and/or insulation, and the displacement amplitude of the loading cycles. A simple analytical method is developed and is found in good agreement with test results. Additionally, numerical modeling is carried out and is also found in good agreement with test results. From the results obtained in this study the authors believe that TRM jacketing may be combined effectively with thermal insulation, increasing the overall strength and energy efficiency of the masonry panels in buildings.

China is facing the development requirements of the dual carbon goal and the construction needs of resilient cities. Currently, high-strength composite structural systems are a feasible solution, but their research and application in the construction field are insufficient, especially for the combination forms of concrete above C100 and steel above Q550. In response to this issue, this paper proposes a new high-performance structural system, namely the composite frame - high-strength steel plate wall core tube resilient structure system, which includes high-strength steel plate (Q550) - ultra-high strength concrete (C100) shear walls, replaceable energy dissipation coupling beams, and composite frames. Taking a 200 meter building as an example, this paper designs and establishes calculation models for a conventional reinforced concrete frame-core tube structure and a high-performance structure based on PKPM software, and establishes elastoplastic analysis models for both based on SAUSAGE software, and then conducts dynamic elastoplastic time history analysis and seismic resilience assessment of structures under design basis earthquakes (DBEs), maximum considered earthquake (MCEs) and extremely rare earthquakes (EREs). Research has shown that compared to conventional structures, new high-performance structures can effectively reduce the size of shear walls, reduce the self-weight of the structure, and enhance the space for building use; The story drift ratio has higher redundancy than specification limits, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance; The seismic resilience has significantly improved, especially in the case of casualties, which can better ensure the safety of people's lives and property.

In the current manuscript, a novel software application for Rapid Damage Assessment of RC buildings subjected to earthquake excitation is presented based on Artificial Neural Networks. The software integrates the use of a novel deep learning methodology for Rapid Damage Assessment into modern software development platforms, while the developed graphical user interface promotes the ease of use even from non-experts. The aim is to foster actions both in the pre- and post- earthquake phase. The structure of the source code permits the usage of the application either autonomously as a software tool for Rapid Visual Inspections of buildings prior to or after a strong seismic event or as a component of Building Information Modelling systems in the framework of digitizing building data and properties. The methodology implemented for the estimation of the RC buildings’ damage states is based on the theory and algorithms of Pattern Recognition problems. The effectiveness of the developed software is successfully tested using an extended, numerically generated database of RC buildings subjected to recorded seismic events

This study investigated and classified typical structures in rural village and analyzed the vulnerability of various typical types of structures. Based on the statistics of earthquake damages with magnitudes above 5 from 1996 to 2013 in China, the damage matrixes of different types of structures in rural village are obtained. And The vulnerability index and the vulnerability equation of structure are crucial to assess the earthquake losses of typical structures under different magnitudes earthquakes. According to the seismic loss of different types of structures under different earthquake magnitudes, there are possible to improve the seismic resilience of the buildings in rural village. Moreover, the regional vulnerability is analyzed by β probability distribution function, and the comprehensive seismic performance index of different types of agricultural buildings in the region is obtained. The main research is to predict the loss of different types of structures under different earthquake magnitudes in the future, and to provide technical support for different types of building in rural village reinforcement.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

Steel damper columns (SDCs) are energy-dissipating members that are suitable for reinforced concrete (RC) buildings and are often used for multistory housing. The evaluation of the peak deformation and hysteretic dissipated energy of such building structures is essential for the rational seismic design of RC buildings with SDCs. In a previous study, the authors proposed an energy-based prediction procedure for the peak and cumulative response of an RC frame building with SDCs. In this procedure, the accuracy of the equivalent velocity of the maximum momentary input energy (V_ΔE1^*)–peak equivalent displacement (D₁^*_max) relationship is essential for high quality predictions. In this article, the V_ΔE1^*–D₁^*_max relationships of RC moment-resisting frames with and without SDCs are invested using a critical pseudo-double impulse (PDI) analysis based on a study by Takewaki and coauthors. The results show that the V_ΔE1^*–D₁^*_max relationship obtained from the critical PDI analysis agrees well with that calculated from the equations proposed in the previous study.

A novel concrete beam-column connection utilizing L-shaped steel bars is proposed to address the growing demand for prefabricated buildings and to ensure good seismic performance in such beam-column structures. After positioning two prefabricated beams with L-shaped tendons into the designated connection points at the top and bottom of the columns, concrete is poured into the post-cast section of the joint and the composite beam area, realizing a connection between the beams and columns. Quasi-static tests were performed on four combined nodes and one cast-in-place node to investigate their failure modes and stress mechanisms. Seismic performance indices, including hysteretic curves, skeleton curves, ductility performance, and energy dissipation capacity, were analyzed. Concurrently, the finite element method (FEM) was employed for parameter analysis. By integrating the test and FEM results, an equation for calculating the shear capacity of the connection was derived. The findings demonstrate that the hysteresis curve of the newly developed prefabricated joints is relatively full, with their overall performance index comparable to that of cast-in-place joints. Additionally, enhancing the post-casting area of concrete, the length of the L-shaped bars, the concrete strength in the composite beam region, the axial compression ratio, or the steel tube dimensions can effectively improve overall performance. The derived equation for the shear-bearing capacity of the connection satisfies design and application requirements.

This paper deals with the quantitative analysis of measured fracture-induced electromagnetic radiation (FEMR) in the vicinity of the Dead Sea Transform using the Angel-M1 instrument, which enables the recording of FEMR signals in a 3D manner. Results show both the possibility of estimating the sizes of micro-fractures that are the sources of the radiation, and of assessing the direction of their location to the measuring device and the range of magnitude Mw of the impending "events" (EQ's) associated with the present FEMR measurements. Moreover, the relation between the measured FEMR activity (the number of FEMR hits per unit time) and the FEMR event magnitudes shows consistency with the Gutenberg-Richter relationship for the region. Such measurements could therefore constitute a preliminary 'field reinforcement' towards an EMR valid method for a real earthquake forecast, which would provide much earlier warnings than the seismic ones. Obviously, the present observed FEMR measurements can only be used as an assessment of the stress concentration and micro-fracturing in the region since they relate to the very initial nucleation phase of a "virtual" (extremely low Richter scale value) earthquake, but they do provide the necessary feasibility test for a prediction method since all lab-measured FEMR features were confirmed also in the field.

This study investigates the interpretability of machine learning (ML) models applied to cumulative damage prediction during a sequence of earthquakes, emphasizing the use of techniques such as SHapley Additive exPlanations (SHAP), Partial Dependence Plots (PDPs), Local Interpretable Model-agnostic Explanations (LIME), Accumulated Local Effects (ALE), Permutation and Impurity-based technique. The research explores the cumulative damage during seismic sequences, aiming to identify critical predictors and assess their influence on the cumulative damage. Moreover, the predictors contribution in respect with the range of final damage is evaluated. Nonlinear time history analyses are applied to extract the seismic response of an eight-story Reinforced Concrete (RC) frame. The regression problem’s input variables are divided into two distinct physical classes: pre-existing damage from the initial seismic event and seismic parameters representing the intensity of the subsequent earthquake, expressed by Park and Ang damage index (DIPA) and Intensity Measures (IMs), respectively. The study offers a comprehensive review of cutting-edge ML methods, hyperparameter tuning, and ML method comparisons. A LightGBM model emerges as the most efficient, among 15 different ML methods examined, with critical predictors for final damage being the initial damage caused by the first shock and the IMs of the subsequent shock: IFVF and SIH. The importance of these predictors is supported by feature importance analysis and local/global explanation methods, enhancing the interpretability and practical utility of the developed model.

In recent decades, widespread damage to structures due to destructive earthquakes has encouraged researchers to use seismic control systems. One of the most important structures is bridges, which should maintain their service after severe earthquakes. One of the ways to control the bridge is to isolation the deck from the substructure, which results in high displacements at different points in the bridge and the residual displacements within the separator itself, thus requiring repair and replacement of these systems after severe earthquakes. Therefore, the use of new seismic separation systems on bridges has always been important. The purpose of this project is to utilize a new memory-shaped seismic separator system to investigate the seismic performance of v-shaped column bridges , in which case the effect of earthquake orientation and its effects on responses the earthquake will also be assessed. Due to the ever-increasing advances in various intelligent materials, such as shape memory alloys, and their unique capacities, such as back-centering, and high fatigue and corrosion resistance, in this study, these materials have been used as a complementary component along with lead core separators. The shape memory alloy has been used as 4 vertical rods that connect two separating parts to each other and in this research the diameter and location of these rods will be calculated using optimization algorithm in Matlab software.

In this study, a tuned mass damper is proposed as a seismic acceleration mitigating technique of an electrical cabinet inside the nuclear power plant. In order to know the mitigation performance, the electrical cabinet and the tuned mass damper were modeled using SAP2000. The sine sweep wave was used to confirm the vibration characteristics of the cabinet over a wide frequency range, and the several various earthquakes were applied to the cabinet to verify the control performance of the tuned mass damper. After analyzing the numerical results, it is summarized that the application of the proposed technique can reduce the acceleration response of the cabinet.

Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of liquid storage tanks founded on half space soil is scrutinized under different earthquake ground motions. To better comparison, the six considered ground motions are classified based on their pulse like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Besides, four types of soils are used to consider wide variety of soil properties. To this end, after deriving the equations of motion, the MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to decrease the impulsive displacement, overturning moment and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period.

The Apennine sector formed by Sannio and Irpinia is one of the most important seismic districts in Italy, representing a good case of study due to the plenty of recorded earthquakes that have therein occurred from Roman times up to nowadays. We have merged the historical record and the new satellite techniques that allow a precise determination of ground movements, and then derived physical dimensions like strain rate. In this way, we have verified that in Irpinia the hazard of new strong shocks forty years after one of the strongest known seismic events in the district is still high. This aspect must be considered very important from many points of view, particularly for Civil Protection plans, as well as civil engineering and urban planning development.

The aim of this study is to present a method for developing fragility curves for soil liquefaction that are consistent with the seismic hazard using Monte Carlo simulation. This method can account for all the uncertainties and variabilities of the input parameters. The seismic parameters of earthquake magnitude (M) and the associated peak ground acceleration (PGA) are considered together for the liquefaction assessment. The liquefaction potential and damages obtained by this method are more realistic. A case study is performed using data from a sand-boil site in Yuanlin, Changhua county, where liquefaction occurred during the Chi-Chi earthquake in Taiwan in 1999. The results show that the liquefaction potential index, IL, the post-liquefaction settlement, St, and the liquefaction probability index, PW, are all suitable parameters for evaluating the liquefaction damages. The fragility curves for soil liquefaction developed by this method can support the performance-based earthquake engineering (PBEE) approach, provide guidance for liquefaction evaluation to the ‘Taiwan Earthquake Loss Estimation System’-TELES, and serve as a basis for scenario simulation and an earthquake early warning system for liquefaction damages.

The prefabricated ECC/RC combined shear wall structure is an innovative prefabricated composite structure with better seismic performance by using ECC materials with better ductility in the main force and energy consumption regions of the prefabricated reinforced concrete (RC) shear wall structure. The key factors controlling the seismic energy dissipation capacity of this kind of structure are the use regions of ECC in composite coupling beams, use regions of ECC in shear walls, strength of ECC, stirrup ratio of coupling beams, strength of longitudinal reinforcement and so on. The parameters affecting seismic energy consumption are quantified by the finite element analysis method. By comparing and analyzing the load-displacement curves, hysteresis curves, energy dissipation capacity and stiffness degradation of the prefabricated ECC/RC combined shear wall structure specimen under these parameters, it is proposed that the best use regions of ECC is the cast-in-situ zone of the coupling beams with the scope of no more than400 mm at the shear walls’ bottom. The strength grade, the strength grade of longitudinal reinforcement, and the stirrup ratio of coupling beams are suggested design as E40, HRB400 and 0.5%, respectively.

The paper explores the potential of a low-cost advanced video-based technique for the assessment of structural damage induced to buildings by seismic loading. A low-cost high-speed video camera was utilized for motion magnification (MM) processing of footages of a two-story reinforced concrete frame building subjected to shaking table tests. The damage after seismic loading was estimated by analyzing the dynamic behavior (i.e. in terms of modal parameters) and the structural deformations of the building in the MM videos. The results by MM were compared for method validation to damage assessment obtained by the analyses of conventional accelerometers and high-precision optical markers tracked by a passive 3D motion capture system. Also, 3D laser scanning to obtain an accurate survey of the building geometry before and after the seismic tests was carried out. In particular, accelerometers were also processed and analyzed by using several stationary and non-stationary techniques with the aim to analyze the linear behavior of the undamaged structure and the nonlinear structural behavior during damaging shaking table tests. The proposed MM-based procedure provided accurate estimate of the main modal frequency and the damage location through the analysis of modal shapes, which were confirmed by advanced analyses of accelerometric data.

The angle of seismic excitation is a significant factor of the seismic response of RC buildings. The procedure required for the calculation of the angle for which the potential seismic damage is maximized (critical angle) contains multiple nonlinear time history analyses using in each one of them different angles of incidence. Moreover, the seismic codes recommend the application of more than one accelerograms for the evaluation of seismic response. Thus, the whole procedure becomes time consuming. Herein, a method to reduce the time required for the estimation of the critical angle based on Multilayered Feedforward Perceptron Neural Networks is proposed. The basic idea is the detection of cases in which the critical angle increases the class of seismic damage compared to the class which arises from the application of the seismic motion along the buildings’ structural axes. To this end, the problem is expressed and solved as Pattern Recognition problem. As inputs of networks the ratios of seismic parameters’ values along the two horizontal seismic records' components, as well as appropriately chosen structural parameters, were used. The results of analyses show that the neural networks can reliably detect the cases in which the calculation of the critical angle is essential.

In order to alleviate the problems regarding conventional damping modeling techniques in nonlinear structural simulations, using concentrated plasticity formulation including rotational end springs with no damping plus middle elastic parts with modified assigned damping has recently been proposed. However, a proper selection for springs’ stiffness is a source of contention. In this paper, the effect of choosing different ratios for springs’ rotational stiffness to the elastic part of the elements on the seismic performance of RC moment frames was investigated. Incremental Dynamic Analysis (IDA) was performed and the derived responses were used for seismic performance assessment methodology. The results demonstrate that using flexible springs may lead to a greatly conservative estimation of collapse capacity, annual losses, and repair costs compared to a rigid one. Due to lack of experimental data, it is not possible to certainly assert the most appropriate ratio. However, such variation in the seismic performance of a building model with different stiffness modification necessitates more investigation on this modeling strategy.

Disparities between fold amplitude (A) and intrusion thickness (Hsill) are critical in identifying elastic or inelastic deformation in a forced fold. However, accurate measurement of these two parameters is challenging because of the limit in separability and detectability for the seismic data. In the TZ-47 exploring area from the Tarim Basin, Northwest China, we combined wireline data and 3-D seismic data, to accurately constrain the fold amplitude and total thickness of sills that inducing the roof uplift. The measurement results show that the forced fold amplitude is 155 m and the total sill thickness is 148.4 m. When using a magma density of 2.7 g/cm3, and solid rock density of 3 g/cm3, the molten magma thickness at the time of intrusion would be 153.8 m, which is almost no difference from the forced fold amplitude. Therefore, the TZ-47 fold is a pure elastic forced fold induced by emplacement of multiple sills. Measurement solely based on seismic data may not be able to detect some thin interlayers and may result in large errors.

Abstract: This paper summarises an early and successful piece of citizen science, performed within The University of Queensland Seismograph Stations (UQSS) observatory, in cooperation with colleagues at CSIRO. It was designed to en-courage young STEM students from Brisbane high schools to engage in “real” re-search, back in 1995. Having completed the project report, their (analog) results sat in a cupboard until the report was dusted off and the project was re-analysed in 2022 by an honors student, considering timely climate change applications for the study. This is a time when science is changing considerably from analog to digital medium and operational methods. The original project was called Earthquake generated T phases on BRS Seismograph (Brisbane, Q’ld)- a predictor for Tasman Sea Tsunamis? [1] Fortunately, seismology is a very collaborative field. The research question has since changed. There is a lot of data analysis involved in the science of recording earthquake signals, with auxiliary definitive catalogues, observers logbooks, housing of the recordings themselves (analog and digital) and the software mediums that change over time. In other words, a lot of headaches can be encountered in longitudinal data collection study such as this. The citizen science students used a pre-prepared decadal collection (1980-90) derived from the BRS observatory data catalogue. BRS is part of the global World-Wide Seismograph Station Network (WWSSN). Currently in Australia, university earth science observatories have diminished, and in their place, public seismic networks (PSN) have evolved, either in back-yard sheds or school science labs. The level of expertise required fits the role of advancing citizen science for a real science advantage. This is a topical citizen disaster preparedness action area for today’s climate emergency, which is threatening the globe and all lifeforms. Citizen engagement or mobilisation is an essential preparedness strategy. Keywords: citizen science 1; seismology 2; earth observation 3; climate change 4; education for sustainable development 5; disaster preparedness 6; disaster alerts 7

This communication investigates possible anomalies in the lithosphere atmosphere and ionosphere on the occasion of the ML=3.3 earthquake that occurred on 1st January 2023 close to Guidonia Montecelio (Rome, Italy). This earthquake followed another event on 23 December 2022 of magnitude ML=3.1 with a very close epicentre (distance less than 1km). Seismological investigations clearly show an acceleration of seismicity in the last six months in the area. Two solutions of fitting time to failure power law on the Cumulative Benioff strain curve are the more likelihood: the ML3.3 of 1 January is the mainshock of seismic sequence or incoming earthquakes of a magnitude of about 4.1 provides a slightly better fit of the seismic data. Further investigation are necessary to assess if the accumulated stress have been totally released or not. No atmospheric anomalies related to this seismic activity have been identified even if some SO2 emissions could come from tectonic or volcanic sources in the South-Tyrrhenian Sea. Swarm satellites' magnetic data shows an anomalous track on 16 December 2022, which is temporally compatible with the seismic acceleration but other sources for the anomalous signal are also possible.

Seismic imaging is the main technology used for subsurface hydrocarbon prospection. It~provides an image of the subsurface using the same principles as ultrasound medical imaging. As for any data acquired through hydrophones (pressure sensors) and/or geophones (velocity/acceleration sensors), the raw seismic data are heavily contaminated with noise and unwanted reflections that need to be removed before further processing. Therefore, the noise attenuation is done at an early stage and often while acquiring the data. Quality control (QC) is mandatory to give confidence in the denoising process and to ensure that a costly data re-acquisition is not needed. QC is done manually by humans and comprises a major portion of the cost of a typical seismic processing project. It is therefore advantageous to automate this process to improve cost and efficiency. Here, we propose a supervised learning approach to build an automatic QC system. The~QC system is an attribute-based classifier that is trained to classify three types of filtering (mild = under filtering, noise remaining in the data; optimal = good filtering; harsh = over filtering, the signal is distorted). The attributes are computed from the data and represent geophysical and statistical measures of the quality of the filtering. The system is tested on a full-scale survey (9000 km²) to QC the results of the swell noise attenuation process in marine seismic data.