Search

The New Zealand Community Fault Model (NZ CFM) is a publicly available representation of New Zealand fault zones that have the potential to produce damaging earthquakes. Compiled through collaborative engagement between New Zealand earthquake-science experts, this first edition (version 1.0) of the NZ CFM builds upon previous compilations of earthquake-source active fault models with the addition of new and modified information. Developed primarily to support an update of the New Zealand National Seismic Hazard Model, the NZ CFM comprises two principal components. The first dataset is a two-dimensional map representation of the surface traces of 880 generalised fault zones. Each fault zone is assigned specific geometric and kinematic attributes, including uncertainties, supplemented with a subjective quality ranking focused primarily on the confidence in assigned slip rates. The second component is a three-dimensional representation of the fault zones as triangulated mesh surfaces that are projected down-dip from the two-dimensional mapped traces to a geophysically-defined maximum fault rupture depth. This article summarises the compilation and parameterisation of the NZ CFM, along with background on its relation to predecessor datasets, and forward applications to probabilistic seismic hazard assessment and physics-based earthquake models currently being developed for Aotearoa New Zealand. [ABSTRACT FROM AUTHOR]

Conditional Spectrum (CS), characterized by a conditional mean and conditional standard deviation, serves as a target spectrum linking seismic hazard information to ground motion selection for seismic demand analysis. Current Ground Motion Selection and Modification (GMSM) methods aim to align with this target spectrum but face challenges due to the limited availability of recorded ground motions and potential modifications, leading to difficulties in ensuring selected ground motions accurately reflect site characteristics. Addressing this issue, the study presents an algorithm to select hazard-consistent CS-based records utilizing a stochastic ground motion model with a dual objective: (1) alleviate the need for scaling during the selection process, and (2) select records consistent with the target hazard and the contributing causal scenarios. To achieve both objectives, the study generates a database of hazard-targeted ground motions utilizing the kriging surrogate with scenarios sampled from the disaggregation matrix. Then, a postprocessing step explicitly considers causative parameters in the selection process. The algorithm's potential to select site-specific ground motions is demonstrated using sites in the Western United States, providing insights into the computational cost and accuracy. Additionally, statistical comparisons are conducted to explore circumstances where similar hazard consistency can be achieved without the postprocessing step, reducing the overall computational cost. Finally, the selected ground motions are favorably compared to those selected through traditional conditional spectrum-based approaches based on their spectral shape and ground motion intensity measures. [ABSTRACT FROM AUTHOR]

Pounding between adjacent structures subjected to earthquake actions can cause significant damage. Due to the many uncertainties inherent to the seismic input and the impact phenomenon, a probabilistic assessment of the occurrence of seismic pounding and of its consequences on the structural performance is necessary. This work analyzes the problem of pounding by considering a single-degree-of-freedom benchmark system surrounded by rigid boundaries and subjected to a stochastic earthquake input. Although simplified, the model is representative of several realistic configurations, such as base-isolated systems surrounded by moat walls or bridge decks near the bridge abutments. The problem is cast in non-dimensional form and a parametric study is carried out to evaluate the influence of the identified non-dimensional input parameters on the statistics of the response. A probabilistic demand model is developed for the impact forces via non-linear regression, with the demand expressed as a function of the identified non-dimensional parameters. This model provides an estimate of median pounding force and of its dispersion given the seismic intensity of the input. Finally, global sensitivity analysis is used to rank the model parameters in terms of their influence on the system performance. [ABSTRACT FROM AUTHOR]

Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical, and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region have become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical, and geotectonical nature. The dataset comprises 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions. [ABSTRACT FROM AUTHOR]

Tsunami inundation maps are crucial for understanding the impact of tsunamis and planning mitigation measures. Our research focuses on creating a database of stochastic tsunami scenarios along the Chilean subduction zone and probabilistic inundation maps for 11 coastal cities. We divided the Chile-Perú subduction zone into four seismic segments based on historical seismicity. Stochastic rupture scenarios, ranging from 8.0 to 9.6 magnitudes, were generated using the Karhunen-Loeve expansion. The Stochastic Reduced Order Model (SROM) helped select representative tsunami scenarios for each segment and magnitude bin. We then used the NEOWAVE model to simulate these scenarios to an inundation level, creating probabilistic tsunami maps for various return periods. Our findings reveal that local geography significantly influences tsunami inundation, with some areas facing high inundation risks while others experience minimal impacts. As a result, a uniform planning and design criterion across the entire country is not advisable; site-specific studies are necessary. These probabilistic scenarios can provide tailored solutions for different Chilean coastal cities, enhancing their resilience. Additionally, this research marks the first comprehensive probabilistic tsunami hazard analysis for the Chilean coast, considering multiple seismic sources, marking a crucial step toward full tsunami risk assessment for coastal communities. [ABSTRACT FROM AUTHOR]

The 2016 magnitude (MW) 5.5 Gyeongju earthquake, which occurred in Korea near assumed epicenters of several substantial historical earthquakes and Quaternary fault segments, underscores the importance of seismic hazard assessment in the region. However, uncertainties about potential seismic sources make evaluating the potential for a moderate-to-large earthquake challenging. Microearthquake monitoring through a dense seismic network can provide crucial insights into the regional seismic characteristics. An extensive temporary seismic array known as the Gyeongju Hi-density Broadband Seismic Network (GHBSN) was established to investigate microearthquake activity in the southeastern Korean Peninsula. This included the zone of aftershocks from the 2016 Gyeongju earthquake sequence. The GHBSN comprises 200 broadband stations located at approximately 4.5 km intervals in an area of approximately 60 × 60 km2 around the epicenter of the mainshock. A total of 4,773 events were detected from November 2017 to December 2021, including 3,935 events within the GHBSN. The detected events were categorized into five seismic regions excluding quarry blasting sites, that is, the 2016 Gyeongju earthquake region, eastern part of the Ulsan Fault, 2017 Pohang earthquake region, eastern offshore Gyeongju, and western part of the Miryang Fault. A local magnitude scale was developed for the southeastern Korean Peninsula using events detected through the GHBSN. This reflects the distance attenuation and site conditions of the GHBSN stations for earthquakes. An event catalog was created using two automatic detection methods based on the measurement of the energy ratio. This provided high-resolution hypocenter parameters at a completeness magnitude (MC) of 0.0 despite the seismic environment of the network being exposed to high cultural noise. The Gutenberg-Richter b-value was estimated as 0.82 ± 0.02 for all events and 1.01 ± 0.02 for those inside GHBSN. This implies that the seismicity reflects a representative intraplate seismic environment. Testing the obtainability of the focal mechanism solutions showed that the GHBSN outperformed the regional network. Depending on the relationship between the magnitude and frequency of earthquakes, a relatively large number of small earthquakes can provide detailed information on the geometric properties of the causative faults and the state of the acting stress. High-precision microearthquake observation and analysis through GHBSN could provide an unprecedented opportunity with seismic datasets to understand the seismogenesis of the southeastern Korean Peninsula, including the zone of aftershocks of the 2016 Gyeongju earthquake. [ABSTRACT FROM AUTHOR]

The Himalayan region and its surrounding area are one of the most seismically active zones in the world which have significant economic and societal impact. It governs the seismicity of highly populous countries like India, China, Pakistan, Nepal, Bhutan and Afghanistan which account for more than 40% population of the world. Therefore, the complex interaction between seismic parameters and transient seismic events needs to be thoroughly addressed at the regional scale. This study highlights the spatial distribution of earthquake hazard parameters and the temporal variation in seismicity of the Himalayas and its nearby regions by employing the maximum likelihood approach using historical records as well as instrumentally recorded earthquake data of the years 1900–2021. An empirical relation is developed to convert the body wave magnitude (Mb) and surface wave magnitude (Ms) to moment magnitude (Mw). The seismic parameters, namely maximum regional magnitude (Mmax), b-value, and mean seismicity rate (λ0), are estimated for 13 defined zones. Further, the seismic behaviours of the study area are evaluated through the return periods (RP) of earthquakes and the fractal dimension (Dc) of the individual zone. Considering the temporal variation of seismicity and RP of Mw ≥ 6, a new index , i.e. earthquake susceptibility index (ESI6), is developed to identify the zones which are susceptible to Mw ≥ 6 earthquakes. The zones: Central Himalayas 2 (CH2), Western Himalayas (WH), North of MCT 1 (NMCT1) and South of MCT 2 (SMCT2) are identified to be highly susceptible to earthquakes of Mw ≥ 6. The present analysis will motivate researchers and engineers from government and non-government organizations to collaborate for improved policy making in the seismically active Himalayan region concerning land-use planning, insurance, and catastrophe preparation. [ABSTRACT FROM AUTHOR]

A five story (G + 4) residential structure is positioned on 15°, 30°, and 45° slopes to be explored in this study in terms of vulnegrability and compared to the same structure resting on flat ground 0°. The RC frame models were constructed in accordance with Eurocode 8 and then subjected through a series of 10 ground motion records. In accordance with Vision 2000 performance limit states (PLS), this research provided the use of nonlinear static analysis (NL-SA) and nonlinear dynamic analysis (NL-DA) methodologies to assess seismic risk performance and vulnerability of structures resting on various slope angles. Incremental Dynamic Analysis (IDA) and Pushover Analysis (POA) capacity curves, as well as the fragility curve and the collapse margin ratio, are generated for the four selected models (M0, M15, M30, M45). The results show that the RC frame model M45, located on a 45°-degree incline, is the most vulnerable to damage. The risk of damage to the RC frame M0 is minimal because it is not elevated off the ground. To this end, the relative degrees of vulnerability among the frames were determined to be as follows: M45 > M30 > M15 > M0. [ABSTRACT FROM AUTHOR]

Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models--which forecast shaking as peak ground acceleration or velocity--and observations--parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes. [ABSTRACT FROM AUTHOR]

Precipitation nowcasting (forecasting locally for 0–6 h) serves both public security and industries, facilitating the mitigation of losses incurred due to, e.g., flash floods and is usually done by predicting weather radar echoes, which provide better performance than numerical weather prediction (NWP) at that scale. Probabilistic nowcasts are especially useful as they provide a desirable framework for operational decision-making. Many extrapolation-based statistical nowcasting methods exist, but they all suffer from a limited ability to capture the nonlinear growth and decay of precipitation, leading to a recent paradigm shift towards deep-learning methods which are more capable of representing these patterns. Despite its potential advantages, the application of deep learning in probabilistic nowcasting has only recently started to be explored. Here we develop a novel probabilistic precipitation nowcasting method, based on Bayesian neural networks with variational inference and the U-Net architecture, named DEUCE. The method estimates the total predictive uncertainty in the precipitation by combining estimates of the epistemic (knowledge-related and reducible) and heteroscedastic aleatoric (data-dependent and irreducible) uncertainties, using them to produce an ensemble of development scenarios for the following 60 min. DEUCE is trained and verified using Finnish Meteorological Institute radar composites compared to established classical models. Our model is found to produce both skillful and reliable probabilistic nowcasts based on various evaluation criteria. It improves the receiver operating characteristic (ROC) area under the curve scores 1 %–5 % over STEPS and LINDA-P baselines and comes close to the best-performer STEPS on a continuous ranked probability score (CRPS) metric. The reliability of DEUCE is demonstrated with, e.g., having the lowest expected calibration error at 20 and 25 dBZ reflectivity thresholds and coming second at 35 dBZ. On the other hand, the deterministic performance of ensemble means is found to be worse than that of extrapolation and LINDA-D baselines. Last, the composition of the predictive uncertainty is analyzed and described, with the conclusion that aleatoric uncertainty is more significant and informative than epistemic uncertainty in the DEUCE model. [ABSTRACT FROM AUTHOR]

This article presents the findings of a study on the directionality effect observed in strong motion records. We set out to establish ratios between several seismic intensity measures that depend on sensor orientation (e.g., GMar, Larger) and others that are orientation-independent (e.g., RotDpp, GMRotDpp, and GMRotIpp), with the intention of proposing multiplicative correction factors. The analysis included an evaluation of the impact of site conditions, ground motion intensity, earthquake magnitude, and hypocentral distance on these ratios. Following a concise overview of the directionality effects and the associated intensity measures, the Costa Rican Strong Motion Database, comprising a total of 4199 horizontal accelerograms (two components), was employed to determine the correction factors. The analysis was carried out for 5% damped response spectra within the 0.01–5 s period range. The study focuses on orientation-independent intensity measures that are derived by combining the maximum values from the recorded motions. In the comprehensive analysis of the complete database, a trend was observed between these intensity measures and the magnitude of the earthquake along with the hypocentral distance. Specifically, records from earthquakes with greater magnitudes exhibited a lower maximum spectral response to the geometric mean of the response spectra of the as-recorded (ar) components ratio (RotD100/GMar), similar to records from earthquakes with larger hypocentral distances. Based on these findings, a proposal was put forth to estimate RotD100 values using GMar values. This ratio can prove useful in transforming data from previous seismic hazard studies, including those applied in many seismic codes, and in defining the maximum anticipated seismic intensity for design purposes in a more straightforward manner. [ABSTRACT FROM AUTHOR]

In the territory of Dushanbe city, the capital of Tajikistan, detailed geological and geophysical data were collected during geophysical surveys in 2019–2020. The data comprise 5 microtremor array measurements, 9 seismic refraction tomography profiles, seismological data from 5 temporary seismic stations for standard spectral ratio calculations, 60 borehole datasets, and 175 ambient noise measurements. The complete dataset for Dushanbe was used to build a consistent 3D geologic model of the city with a size of 12 × 12 km2. The results of the seismological and geophysical surveys were compared and calibrated with borehole data to define the boundaries of each layer in the study area. The Leapfrog Works software was utilized to create a 3D geomodel. From the 3D geomodel, we extracted six 12 km long 2D geological cross-sections. These 2D geological cross-sections were used for 2D dynamic numerical modeling with the Universal Distinct Element Code software to calculate the local seismic response. Finally, the dynamic numerical modeling results were compared with the amplification functions obtained from the seismological and ambient noise data analysis. The 2D dynamic numerical modeling results allowed a better assessment of the site effects in the study area to support seismic microzonation and the determination of local peak ground acceleration changes in combination with regional seismic hazard maps. In addition, our results confirm the strong seismic amplification effects noted in some previous studies, which are attributed to the influence of local topographic and subsurface characteristics on seismic ground motions. [ABSTRACT FROM AUTHOR]

We applied an interdisciplinary approach to analyze the late Quaternary activity of the Sava Fault in the Slovenian Southern Alps. The Sava Fault is an active strike-slip fault, and part of the Periadriatic Fault System that accommodated the convergence of Adria and Europe. It is one of the longest faults in the Southern Alps. Using high-resolution digital elevation models from lidar and photogrammetric surveys, we were able to overcome the challenges of assessing fault activity in a region with intense surface processes, dense vegetation, and relatively low fault slip rates. By integrating remote sensing analysis, geomorphological mapping, structural geological investigations, and near-surface geophysics (electrical resistivity tomography and ground penetrating radar), we were able to find subtle geomorphological indicators, detect near-surface deformation, and show distributed surface deformation and a complex fault pattern. Using optically stimulated luminescence dating, we tentatively estimated a slip rate of 1.8 ± 0.4 mm/a for the last 27 ka, which exceeds previous estimates and suggests temporal variability in fault behavior. Our study highlights the importance of modern high-resolution remote sensing techniques and interdisciplinary approaches in detecting tectonic deformation in relatively low-strain rate environments with intense surface processes. We show that slip rates can vary significantly depending on the studied time window. This is a critical piece of information since slip rates are a key input parameter for seismic hazard studies. [ABSTRACT FROM AUTHOR]

Seismic risk assessment of building portfolios has been traditionally performed using empirical ground motion models, and scalar fragility and vulnerability functions. The advent of machine learning algorithms in earthquake engineering and ground motion modelling has demonstrated promising advantages. The aim of the present study is to explore the benefits of employing artificial neural networks (ANNs) in earthquake scenarios for spatially-distributed building portfolios. To this end, several recent major seismic events in the Balkan region were selected to assess damage and economic losses, considering different modelling approaches. For the assessment of the seismic demand, the ANN developed in the companion study and common ground motion models for Europe were adopted. For the vulnerability component, recent ANN models and existing scalar fragility and vulnerability functions for the Balkans were used. The estimates of all modelling cases were compared against the aggregated damage and economic loss data observed in the aftermath of these events. The findings of this study suggest that overall, the ANNs led to damage and economic loss estimates closer to the observations. [ABSTRACT FROM AUTHOR]

The calculation of the spatial distribution of ground motion is one of the most important steps in earthquake scenarios. The advancements in machine learning algorithms and the release of new ground motion data can enable improvements in the reliability and accuracy of this component. We developed an artificial neural network (ANN) ground motion model using a compiled database from two subsets with measured Vs30 from the Pan-European strong motion database and the NGA-West2 database. The ANN model employs five input parameters: moment magnitude (Mw), hypocentral depth, Joyner–Boore distance (Rjb), shear wave velocity in the top 30 m (Vs30), and faulting type. The outputs of the ANN are the RotD50 horizontal components of common intensity measures used in seismic risk assessment: PGA, PGD, PGV, Arias Intensity, and 5% damped spectral acceleration at 27 periods from 0.01 to 4.0 s. A mixed-effects modelling approach was followed to train the ANN and partition the ground motion variability into between-event and between-site terms. The input parameter scaling relationships were studied and demonstrated physically sound trends of the ground motion with respect to Mw scaling, distance attenuation, and site amplification. The predicted median response spectra for several combinations of Mw and Rjb were compared to common ground motion models for Europe, and the results are discussed. The developed ANN is used in a companion study to calculate the hazard footprints for several historical earthquakes in the Balkan region. [ABSTRACT FROM AUTHOR]

In probabilistic coastal hazard assessments based on the Joint Probability Method, historical storm data is used to build distribution models of tropical cyclone atmospheric parameters (i.e., central pressure deficit, forward velocity, radius of maximum wind, and heading direction). Recent models have used a range of assumptions regarding the dependence structure between these random variables. This research investigates the performance of a series of joint distribution models based on assumptions of parameter independence, partial-dependence (i.e., dependence between only central pressure deficit and radius of maximum wind), and full dependence (i.e., dependence between each pair of tropical cyclone atmospheric parameters). Full dependence models consider a range of copula models, such as the Gaussian copula and vine copulas that combine linear-circular copulas with Gaussian or Frank copulas. The consideration of linear-circular copulas allows for the characterization of correlation between linear variables (e.g., central pressure deficit) and circular variables (e.g., heading direction). The sensitivity of the results to different joint distribution models is assessed by comparing hazard curves at representative locations in New Orleans, LA (USA). The stability of hazard curves generated using a Gaussian copula considering variation in the selection of the zero-degree convention is also assessed. The tail dependence between large central pressure deficit and large radius of maximum wind associated with various copula models are also compared using estimated conditional probability. It is found that the linear-circular Frank vine copula model improve the stability of hazard curves and maximize tail dependence between large central pressure deficit and large radius of maximum wind. However, the meta-Gaussian copula model exhibits performance within this study region that was generally consistent with the tested vine copulas and have the advantage of being easier to implement. [ABSTRACT FROM AUTHOR]

For regional hazard analysis or engineering applications, it is necessary to simulate a group of correlated ground motions containing information from given recordings. A new method is presented to conditionally generate ground motions at unobserved points using actual recordings in this localized region. This method is based on an extension of the traditional conditional simulation using a wavelet packet. Utilizing the advantages of wavelet-packet transformation, the time and frequency characteristics of ground motions are effectively identified. Besides by decomposing the signal into non-overlapping sub-frequency bands, it is possible to conditionally simulating stationary, space-time, and Gaussian random fields. These simulated motions are consistent with the actual recordings in terms of temporal variations in the frequency domain and its design spectrum, and their coherence functions satisfy the target coherence values. Two numerical examples have been provided to illustrate the capability of the proposed method: the simulation of ensembles of earthquake accelerograms using actual recordings and blind tests in SMART-1 array. [ABSTRACT FROM AUTHOR]

Earthquake hypocentres are routinely obtained by a common inversion problem of P - and S -phase arrivals observed on a seismological network. Improving our understanding of the uncertainties associated with the hypocentral parameters is crucial for reliable seismological analysis, understanding of tectonic processes and seismic hazard assessment. However, current methods often overlook uncertainties in velocity models and variable trade-offs during inversion. Here, we propose to unravel the effects of the main sources of uncertainty in the location process using techniques derived from the Global Sensitivity Analysis (GSA) framework. These techniques provide a quantification of the effects of selected variables on the variance of the earthquake location using an iterative model that challenges the inversion scheme. Specifically, we consider the main and combined effects of (1) variable network geometry, (2) the presence of errors in the analyst's observations and (3) errors in velocity parameters from a 1-D velocity model. These multiple sources of uncertainty are described by a dozen of random variables in our model. Using a Monte Carlo sampling approach, we explore the model configurations and analyse the differences between the initial reference location and 100 000 resulting hypocentral locations. The GSA approach using Sobol's variance decomposition allows us to quantify the relative importance of our choice of variables. It highlights the critical importance of the velocity model approximation and provides a new objective and quantitative insight into understanding the sources of uncertainty in the inversion process. [ABSTRACT FROM AUTHOR]

For reinforced concrete (RC) column with biaxial eccentricity, the conventional design methods usually use the fixed eccentricity criterion to check its resistance, which may underestimate the variations of column resistance. Based on the load statistics compatible with the codes, the random properties of biaxial eccentricity are analyzed with Monte Carlo simulation (MCS) for representative columns in regular frame structures under both vertical load and wind load. Then, the tested capacity results of 103 relevant column specimen are collected from literatures. The uncertainty of the resistance model is analyzed for the reciprocal load method in code ACI 318-14. Based on the criterion of both random eccentricity and fixed eccentricity, the probability regarding load bearing capacity exceedance is analyzed for columns by MCS with different design parameters (e.g. axial compression ratio, etc.). The results indicate that based on the prescribed load statistics, the random properties of eccentricities along two principal directions are mainly controlled by the stochastic wind load, leading to that the eccentricities along two principal directions show an approximate perfect correlation; the random biaxial eccentricity has a significant influence on resistance variations and the maximum coefficient of variation is as large as 0.73. [ABSTRACT FROM AUTHOR]

In order to avoid the casualties caused by damaged buildings during strong earthquakes, it's important and essential to understand the seismic design specifications of buildings. The motion of a building depends on the interferometry of building and ground motion, the coupling between building and ground, and the mechanical properties of the building. We applied deconvolution technique to the motion recorded to separate the building response and calculated the structural parameters (including traveling wave velocity, resonant frequency and attenuation parameter). Therefore, we can check medium's state by tracking these parameters to avoid damaged building collapse in the next mega-earthquake. We deployed a seismograph array in the building to record the earthquakes and few months of ambient noise data. In addition, we divided the structure into lower and higher floors to calculate the layering velocity. We found that the wave velocities of the lower and higher floors are significantly different but the former exhibit stable variation. For the monitoring phase, we tried different stacking time-lengths and calculated the related traveling wave velocities which are similar to the analysis in earthquakes. From the above results, we concluded that the physical parameters of the building can monitor the healthy condition of structure. Finally, we hope these results would be helpful to build a long-term monitoring of building's healthy status and the assessment of seismic hazard. [ABSTRACT FROM AUTHOR]

The establishment of a unified earthquake catalog is a basic requirement for attaining a detailed seismological analysis and an improved seismic hazard assessment. Accordingly, the current research paper aims to present a reliable instrumental unified earthquake catalog for the northern part of Algeria. This unified catalog is compiled using regional empirical relationships derived from converting different magnitude scales to an advanced physical-based moment magnitude scale suggested in the recent literature and denoted by Mwg. The regression methodology used in this study is called the New General Orthogonal Regression approach (N.GOR), which was selected since it is the most trustworthy procedure for scaling the magnitudes to Mwg. To highlight the significance of using the N.GOR, the obtained outcomes of the scaling relations were compared with those issued from the conventional general orthogonal regression (GOR) method, which is deemed to be the most dependable methodology used worldwide for magnitude conversion problems. The unified earthquake catalog was assembled from 1954 to 2022. Reliably converting the original magnitudes into homogenized moment magnitude leads to a complete and consistent unified earthquake catalog. Indeed, the unified moment magnitude catalog presented in this paper could provide reliable data for studying earthquakes distribution and the assessment of seismic hazards in the north of Algeria. [ABSTRACT FROM AUTHOR]

We present a new geodetic strain rate and rotation rate model for Greece that has been derived using a highly dense GPS velocity field. The spatial distribution and the resolved rates of the various velocity gradient tensor quantities provided updated constraints on the present‐day upper crustal deformation in the region and revealed new details not reported previously. The spatial distribution of the second invariant demonstrated that the overall magnitude of strain rates is highest across two well‐defined provinces. The first follows the North Anatolian Fault and its two branches within the north Aegean, crosses central Greece and through the Gulf of Corinth it terminates in western Greece, while the second encompasses the extensional province of western Turkey and the eastern Aegean Sea islands. Our estimates revealed that shearing affects some of the fault‐bounded grabens of central Greece that lie to the SW of the North Aegean Basin implying considerable oblique extension. We identified a narrow region of counterclockwise rotation whose location and kinematics have been induced by the net effect across the intersection of the clockwise rotating domains of western and central Greece. The Aegean microplate and the Anatolian plate are separated by a wide transition zone which accommodates the curved stretching of the entire plate system. In both edges of the Hellenic forearc the dominant mode of crustal strain is E‐W extension. We found that earthquakes of M ≥ 5.6 are spatially well‐correlated with high‐strain areas, indicating that strain rate mapping could be used to inform future probabilistic seismic hazard analyses. Plain Language Summary: Greece and its surroundings comprise a region of elevated seismic hazard because of the intense active deformation that is accumulated in earth's crust over time and which is expected to be released as earthquakes of various magnitudes. Given the importance of this relationship, we used a dense data set of GPS velocities to gain insight into the spatial distribution and patterns of the present‐day strain and rotation rates. We found that deformation is mostly concentrated across two zones. The first crosses the North Anatolian Fault, enters the north Aegean Sea, continues in central Greece and terminates in western Greece, while the second encompasses the eastern Aegean Sea islands and western continental Turkey. Across the first zone, the crust experiences various deformation modes due to the interaction of large lithospheric‐scale tectonic structures with smaller regions of localized faulting. Within the second zone, the crust is stretching in response to differences in direction and rate of movement between the Aegean microplate and the Anatolian plate. Comparison of strain rates with seismicity revealed that earthquakes with M ≥ 5.6 predominantly occur within high‐strain areas, giving implications that knowledge of the spatial distribution of tectonic deformation can augment seismic hazard analyses. Key Points: We present an improved geodetic strain and rotation rate model for Greece which reveals new details about active deformationThe strain rate field of Greece is a superposition of short‐ and long‐wavelength signals driven by local forces and large‐scale tectonicsEarthquakes over M 5.6 correlate well with high strain rates and consistently occur at areas where the second invariant exceeds 40 nstrain/yr [ABSTRACT FROM AUTHOR]

Large block‐bounding faults on the Tibetan plateau are significant geological structures that accommodate tectonic movements and accumulate stress, leading to large earthquakes. Quantifying the interseismic slip deficit rate helps to better assess the earthquake potential. We combine available InSAR (2015–2020) and interseismic GPS data to determine fault coupling along 14 major block‐bounding faults. Spatially dense InSAR measurements remarkably improve the resolution of the coupling model. Combined with a GPS‐constrained block model, we examine the performance of the inversion approach with the stress constraint and the common Laplacian smoothing based on both synthetic tests and real data. We suggest that, for continental strike‐slip faults, adding the stress constraint can mitigate unphysical coupling distributions due to unreasonable assumptions or modeling artifacts, reducing the model uncertainty and improving the accuracy of the coupling model. This is particularly useful for segments featured by a highly heterogeneous distribution of coupling along the transition zone from locking to creeping region, partially‐coupling segment, and junction zone between main and subsidiary faults. We present a large‐scale fault coupling map along the major block‐bounding faults on the northeastern and eastern Tibetan plateau, highlighting the distinct degrees of fault coupling and lateral variations. The collage of coupling maps along different faults demonstrates the kinematic features over a broad time scale during earthquake cycles ranging from early to late interseismic phases, such as the segments ruptured during the 2001 Kokoxili earthquake and the 1920 Haiyuan earthquake. Plain Language Summary: Large faults at the boundary of blocks accommodate a significant portion of the relative movement between adjacent blocks and accumulate tectonic stress during the interseismic period. Consequently, these faults have a high potential to generate large earthquakes. To evaluate the distribution of strain accumulation, we analyze InSAR (2015–2020) and interseismic GPS measurements to construct a coupling model, which tells us the extent to which two blocks are locked together and accumulate stress before the next earthquake. We focus on 14 major faults on the eastern and northeastern Tibetan plateau. The addition of the spatially dense InSAR data helps to resolve the coupling distribution in greater detail, where GPS observations are limited. We evaluate different approaches to determine fault coupling, including stress constraints and smoothing techniques. Our findings indicate that adding a stress constraint performs better than the smoothing operator and helps mitigate physically unrealistic coupling distributions in the inversion using the spatial smoothing method. The stress constraint improves the accuracy of the coupling model. Based on the stress‐constrained inversion, we present a comprehensive fault coupling map in the northeastern and eastern Tibetan plateau, highlighting the spatial variations of fault coupling, which can be used in earthquake hazard assessment. Key Points: Stress constraints can mitigate unphysical coupling distributions and reduce the uncertainty of the coupling model for continental faultsWe highlight the improvement when using stress constraints in the case of sharp coupling contrasts along the strike‐slip faultWe provide a new coupling model along 14 major block‐bounding faults on the eastern and northeastern Tibetan plateau [ABSTRACT FROM AUTHOR]

Changes in deviations from the background values of the parameters of the sporadic E ionosphere (Es) are studied: the effective (virtual) height h'Es and limiting reflection frequency (foEs). Basically, the analysis was carried based on hourly measurement data from several Japanese ground stations for vertical sounding of the ionosphere in order to identify possible short-term ionospheric earthquake precursors with intermediate (from 60 to 300 km) hypocentral depths. All known events (12 earthquakes, from 1969 to 2022) are considered for which the necessary ionospheric data in the Japan region and magnitudes (M) ranging from 6.5 to 7.6 are available. From coincidence of the maxima in changes in the considered Es characteristics on the same day at pairs of stations separated by hundreds of kilometers, the time of appearance of possible ionospheric earthquake precursors was recorded. According to the ionospheric data available during the preparation period for the studied earthquakes, a tendency has been identified according to which the time the moment of the main influence is anticipated depends on the magnitude of the impending earthquake. Similarities and differences in the responses of the ionosphere to the preparation of surface (crustal) earthquakes and earthquakes with an intermediate hypocentral depth are revealed. Another tendency is also revealed: earlier appearance of the identified earthquake precursors with increasing hypocentral depth for earthquakes with an intermediate hypocentral depth at the same distances from the epicenter to the observation point. [ABSTRACT FROM AUTHOR]

Establishing the absolute age of palaeoearthquakes is of great significance for the assessment of the seismicity and seismic hazards of a region. As such, several different geochronological techniques to date earthquake-related material have been developed to provide answers on the time of past earthquakes. The present study is part of a wider palaeoseismic research project conducted in the Nojima Fault Zone (NFZ), where the 1995 Mw 6.9 Kobe (Japan) earthquake was triggered, to assess the suitability of the isothermal thermoluminescence (ITL) dating technique on fine-grained quartz and medium-grained feldspar and to provide a sequence of ages for fault-rock samples separated from a drilled core that was retrieved from a depth of ~506 m. Our analysis reveals that ITL can produce consistent dating results and can be considered a reliable luminescence technique for the absolute dating of fault-gouge material. The produced ITL ages signified the existence of repeated seismic events within the NFZ that took place through the late Pleistocene period, with gouge ages spanning from 78.6 ± 4.2 to 13.4 ± 1.4 ka; however, overestimation of the produced ITL dating results may be apparent. Nonetheless, even though some degree of overestimation is considered, ITL dating results denote the oldest possible age boundary of formation (or luminescence signal resetting) of the collected fault-gouge layers. [ABSTRACT FROM AUTHOR]

Numerous ground-motion models (GMMs) that predict the intensities of surface ground motions have been previously developed based on regression analysis (RA). This study develops GMMs to estimate 5% damped pseudo-spectral accelerations (PSAs) for 30 periods (0.01–7.0 s) for within-rock ground motions, based on machine learning (ML) methods (i.e., two ensemble methods (random forest (RF) and gradient boosting (GB)) and an artificial neural network (ANN)). GMMs are developed separately for four earthquake types (main and aftershocks of active crustal region events and those of subduction zone interface events), considering the differences in the characteristics of each earthquake type. We utilize 20,041 ground motions recorded at 575 borehole stations in Japan during 602 earthquakes with moment magnitudes greater than 5.0 and rupture distances shorter than 300 km. The prediction performances of GMMs based on RF, GB, ANN, and RA are evaluated by the standard deviations of the total, between-event, and within-event residuals. The GMMs based on the three ML methods (RF, GB, and ANN) perform better than the RA-based models. The RF-based GMMs resulted in the most accurate prediction of the PSAs of within-rock ground motions with a small bias and variance, which can enhance the seismic designs and seismic hazard assessments for underground structures. [ABSTRACT FROM AUTHOR]

An optimisation-based calibration technique, using the area metric, is applied to determine the input parameters of a stochastic earthquake-waveform simulation method. The calibration algorithm updates a model prior, specifically an estimate of a region's seismological (source, path and site) parameters, typically developed using waveform data, or existing models, from a wide range of sources. In the absence of calibration, this can result in overestimates of a target region's ground motion variability, and in some cases, introduce biases. The proposed method simultaneously attains optimum estimates of median, range and distribution (uncertainty) of these seismological parameters, and resultant ground motions, for a specific target region, through calibration of physically constrained parametric models to local ground motion data. We apply the method to Italy, a region of moderate seismicity, using response spectra recorded in the European Strong Motion (ESM) dataset. As a prior, we utilise independent seismological models developed using strong motion data across a wider European context. The calibration obtains values of each seismological parameter considered (such as, but not limited to, quality factor, geometrical spreading and stress drop), to develop a suite of optimal parameters for locally adjusted stochastic ground motion simulation. We consider both the epistemic and aleatory variability associated with the calibration process. We were able to reduce the area metric (misfit) value by up to 88% for the simulations using updated parameters, compared to the initial prior. This framework for the calibration and updating of seismological models can help achieve robust and transparent regionally adjusted estimates of ground motion, and to consider epistemic uncertainty through correlated parameters. [ABSTRACT FROM AUTHOR]

A homogeneous earthquake catalogue is necessary to conduct a thorough seismological investigation and improve seismic hazard assessment. Therefore, the present study intends to determine the influence of magnitude homogenization based on different regression methods on the seismicity parameters. The earthquake catalog of the Bihar, India region has been used for the study. An events data catalogue consisting of 4001 events has been compiled over the period 1911–2023. The data is primarily sourced from international and local databases have been assembled to provide a comprehensive overview of seismic activity within the study area. Empirical relationships have been derived between moment magnitude and commonly used local and global magnitude scales by performing non-linear regressions using chi-square regression method (CSQ) and ordinary least-square regression method (OLS). Measurement error for both dependent and independent variables of various data sets was calculated for the CSQ process. In order to address the non-linear nature of the correlations, we used curvilinear models, namely, the exponential model (EXP), which was recently introduced by the authors of the global catalogue supported by the global earthquake model (GEM) foundation. The use of CSQ method reduces the bias created by OLS method for defining the nonlinearity of the relationship. Seismicity parameters, including the magnitude of completeness (Mc) and a and b values of the Gutenberg-Richter recurrence model, have been calculated for homogenised undeclustered and declustered catalogue spanning five specific time periods. Declustering has been performed to isolate the foreshocks and aftershocks from the mainshocks. The observed changes in the Mc and b values are found to be dependent on the introduction of more recent data over time. The study area has been divided into eight seismogenic zones based on the geographic variations in earthquake occurrence and the prevailing tectonic conditions. The estimation of Mc, b, and a values has been conducted for each zone, and the analysis has been performed to examine the variations in these parameters. Derived equations serve as valuable tools for assessing and analysing seismic hazards in the north India and the central Himalayas region. [ABSTRACT FROM AUTHOR]

Performance-based design establishes performance objectives in terms of earthquake intensities. Damage limit states depend on the building demands in the nonlinear range of behavior when subjecting the structure to a suite of seismic records. Most of world databases have strong-motions recorded from small- and moderate-magnitude earthquakes that need to be scaled when studying the expected building performance under maximum considered earthquake. Scaling accelerograms is a frequent activity in nonlinear analysis of structures, and different techniques based on several intensity measures have been used, without a general consensus to select the most appropriate scaling methodology. This study shows the variability in the seismic performance assessment of reinforced concrete buildings of different heights, symmetrical in plan and regular in elevation, on four seismic zones, when using scaled accelerograms for a maximum considered earthquake, assumed for a return period of Tr = 2500 years. Ten methodologies frequently used in the literature are analyzed to evaluate inter-story drift ratio and floor acceleration demands of buildings subjected to a suite of near-, medium- and far-fault interplate earthquakes. The results show different expected damage limit states as a function of the scaling technique used. Additionally, some scaling techniques consistently generate higher seismic demands regardless of the seismic location of the buildings, whereas another group produces quite similar demands. Moreover, a building could be placed in the slight damage limit state or in a zone of extensive damage depending on the scaling technique used. [ABSTRACT FROM AUTHOR]

When new seismic hazard estimates are published it is natural to compare them to existing results for the same location. This type of comparison routinely indicates differences amongst hazard estimates obtained with the various models. The question that then arises is whether these differences are scientifically significant, given the large epistemic uncertainties inherent in all seismic hazard estimates, or practically important, given the use of hazard models as inputs to risk and engineering calculations. A difference that exceeds a given threshold could mean that building codes may need updating, risk models for insurance purposes may need to be revised, or emergency management procedures revisited. In the current literature there is little guidance on what constitutes a significant or important difference, which can lead to lengthy discussions amongst hazard modellers, end users and stakeholders. This study reviews proposals in the literature on this topic and examines how applicable these proposals are, using, for illustration purposes, several sites and various seismic hazard models for each site, including the two European Seismic Hazard Models of 2013 and 2020. The implications of differences in hazard for risk and engineering purposes are also examined to understand how important such differences are for potential end users of seismic hazard models. Based on this, we discuss the relevance of such methods to determine the scientific significance and practical importance of differences between seismic hazard estimates and identify some open questions. We conclude that there is no universal criterion for assessing differences between seismic hazard results and that the recommended approach depends on the context. Finally, we highlight where additional work is required on this topic and that we encourage further discussion of this topic. [ABSTRACT FROM AUTHOR]

The regional seismic risk assessment plays an important role in the disaster prevention and mitigation. The accurate time-history analysis for a region provides an important data base for regional seismic risk assessment. However, an accurate calculation method is limited, then, its accuracy still lacks validation. Meanwhile, there is also a lack of risk assessment methods and indicators applicable to the regional accurate time-history analysis, both of which hinder the seismic risk assessment. In this paper, a regional-scale time history analysis-driven method is proposed for the quantitative evaluation of regional seismic damage risk and verified with a real earthquake damage survey. First, the regional time history analysis method is introduced, including the automatic modeling, response calculating, result analysis and 3-D visualization modules. Second, a calculation method for seismic damage degrees (DD) of buildings is introduced. Subsequently, the probabilistic models of each DD under the ground motions with a specific intensity are calculated based on regional-scale nonlinear time history analysis. Next, the concept of the three-level seismic damage risk is offered, then a determining workflow of seismic damage risks is proposed based on the code-abiding three-level design requirement. Afterward, the regional seismic damage index is suggested for the quantitative evaluation of earthquake-induced damage risk. Finally, the actual seismic damage database of 192 buildings in epicenter of Ludian Earthquake is established through on-site investigations, then used to verify the regional simulation's accuracy. Consequently, it could be an aid to accurately present seismic damage distribution assessments and effectively develop seismic risk mitigation strategies. [ABSTRACT FROM AUTHOR]

This study provides a discussion using a database of historic masonry bell towers struck by past Italian earthquakes, which is the result of an extensive literature review on post-earthquake reconnaissance reports and scientific publications. The observed damage is analysed to give an insight into the seismic behaviour and vulnerability of this peculiar building typology. To this end, a macro-scale approach is adopted, two distinct damage mechanisms are identified and evaluated, and a damage index for each tower is computed. This enables to develop the damage probability matrices, providing the frequency of damage occurrence. Moreover, vulnerability and fragility curves are derived to help the prediction of future possible damage scenarios. The developed vulnerability and fragility curves are compared with the mean damage observed in the samples included in the database. This comparison allowed to check the robustness of rapid procedures today available in the field of seismic risk assessment for the specific case of historic masonry towers. [ABSTRACT FROM AUTHOR]

A resilience-incorporated risk assessment framework is proposed and demonstrated in this study to manifest the advantageous seismic resilience of precast concrete frame (PCF) structures with "dry" connections in terms of their low damage and rapid recovery. The framework integrates various uncertainties in the seismic hazard, fragility, capacity, demand, loss functions, and post-earthquake recovery. In this study, the PCF structures are distinguished from ordinary reinforced concrete frame (RCF) structures by characterizing multiple limit states for the PCF based on its unique damage mechanisms. Accordingly, probabilistic story-wise pushover analyses are performed to yield story-wise capacities for the predefined limit states. In the seismic resilience analysis, a step-wise recovery model is proposed to idealize the functionality recovery process, with separate considerations of the repair and non-repair events. The recovery model leverages the economic loss and downtime to delineate the stochastic post-earthquake recovery curves for the resilience loss estimation. As such, contingencies in the probabilistic post-earthquake repairs are incorporated and the empirical judgments on the recovery parameters are largely circumvented. The proposed framework is demonstrated through a comparative study between two "dry" connected PCFs and one RCF designed as alternative structural systems for a prototype building. The results from the risk quantification indicate that the PCFs show reduced loss hazards and lower expected losses relative to the RCF. Particularly, the PCF equipped with energy dissipation devices at the "dry" connections largely reduces the expected economic loss, downtime, and resilience loss by 29%, 56%, and 60%, respectively, compared to the RCF. [ABSTRACT FROM AUTHOR]

Utilizing an updated dataset of 145 GNSS surface velocities, this study examines the fault slip rate and fault geometry along the Main Himalayan Thrust (MHT) in the central Himalaya. Employing a Bayesian inversion model, the present analysis reveals that the upper portion of the MHT ramp exhibits full locking, while the lower flat displays creeping motion. The estimated locking depth and fault depth of MFT range from 4.3 ± 2.6 km to 9.7 ± 2.2 km and 13.5 ± 3.1 km to 15.8 ± 1.9 km, respectively, along the central Himalaya. Further, the slip rate along the transition zone lies in the range of 1.4 ± 0.8 mm/yr to 2.7 ± 0.5 mm/yr. Considering the amount of uncertainties as ~1–2 mm/yr in GNSS velocities, the study suggests that the transition zone along the middle flat of the MHT also exhibits locking behavior. Thus, the estimated locking depth extends to ~15.0 km down-dip and covers a horizontal distance of ~90 km (locking line) on the surface, reaching the foothills of the Higher Himalaya. Furthermore, along the deeper flat of the MHT, the slip rate ranges from 19.4 ± 2.5 mm/yr in the west to 12.8 ± 1.6 mm/yr in the east along Nepal Himalaya. The analysis also calculates the slip deficit rate along the MHT fault plane, revealing values of ~15.1 mm/yr in western Nepal, ~12.7 mm/yr in central Nepal, and ~10.6 mm/yr in eastern Nepal. These slip deficit rates across different segments of central Nepal indicate the potential for large earthquakes in the region. The results are further supported by a resolution test using a checkerboard synthetic model, demonstrating the capability of the GNSS network to capture the slip rate along the MHT. These findings inevitably contribute to a comprehensive assessment of the seismic hazard potential in the central Himalayan region. [ABSTRACT FROM AUTHOR]

The article focuses on synthesizing research on the seismotectonics of the San Andreas Fault System within the San Gorgonio Pass region of Southern California. It explores the complex fault geometry, slip distribution, and seismic hazard implications through multidisciplinary studies, including geology, geophysics, and modeling. It aims to enhance understanding of fault behavior and earthquake risk assessment, serving as a model for studying restraining bends in strike-slip faults globally.

To consider the influence of epistemic uncertainties in both seismic hazard and numerical simulation on seismic risk of subway station structures, the uncertainties mentioned above are uniformly characterized as the epistemic uncertainty of seismic demand of subway station structures from the perspective of uncertainty propagation in this paper. On this basis, the analytical formulations of seismic risk considering simultaneous aleatory and epistemic uncertainties are derived. The validity of the derived analytical formulations is verified by the Monte Carlo simulation and the influences of epistemic uncertainty on the seismic risk of subway station structure are further discussed. [ABSTRACT FROM AUTHOR]

This study develops a methodology for conducting a quantitative seismic risk assessment for shallow-buried tunnels that are induced by active fault dislocations. A case study for a tunnel crossing a strike-slip fault zone is performed using this method. The fault-tunnel crossing angle, the bedrock overburden thickness, the tunnel burial depth, the lining thickness, and the soil properties parameters are analysed in terms of their effects on the seismic responses, fragility curves, and seismic risks for the tunnels. This methodology could quantify the seismic risk of existing metro tunnels that pass through active fault zones, and could also assist in the establishment of a benchmark tunnel design for designing a tunnel that passes through an active fault zone. [ABSTRACT FROM AUTHOR]

Railway alignment optimization in earthquake‐prone mountainous (EPM) regions should quantify and trade off construction investments and seismic risks. Unfortunately, slight attention has been previously devoted to this trade‐off. To this end, based on the FEMA‐P58 methodology, a net present value (NPV) model of risk avoidance is presented and solved. In the model, alignment alternatives are first segmented into structural groups with different probabilistic seismic fragility curves, which are then used to generate structural repair cost and repair time curves. Afterward, a probabilistic seismic hazard curve is introduced to estimate the expected annual repair cost and time for computing railway direct and indirect seismic losses. Hence, the railway total annual loss caused by seismic activity can be obtained. Next, a benefit–cost analysis is performed to combine construction cost and seismic loss as the risk‐cost NPV. To optimize this objective function, a particle swarm algorithm is used as the basic approach. For implementing the probabilistic seismic performance analysis, a Monte Carlo simulation (MCS) is employed as the risk assessment module. Furthermore, due to the computationally intensive nature of MCS, a CPU‐based parallelization is embedded into the algorithm to expedite the search. Finally, the proposed model and method are applied to a representative real‐world railway case in an EPM region. Their effectiveness is discussed and verified in five experiments, including algorithm convergence analysis, alignment solution comparison, seismic risk interpretation, computational efficiency test, and a specific sensitivity analysis. [ABSTRACT FROM AUTHOR]

Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using various intensity measures to estimate and forecast the seismic hazard of RC structures can contribute to the development of typical structural seismic resilience and vulnerability models. However, traditional empirical and analytical vulnerability studies rely more on field observation data and seismic risk algorithms and less on numerical simulation analysis for validation and optimization, resulting in limitations and fuzziness in the accuracy of the developed structural risk models. To explore the damage modes of RC frame structures under different intensities, this paper innovatively combines numerical model algorithms with empirical vulnerability methods to conduct empirical vulnerability and numerical simulation analyses on RC structures. Using probability statistics and nonlinear regression analysis methods, a prediction model for estimating the fragility of RC structures was proposed, and 858 RC structure damage samples from a typical city (Dujiangyan) during the Wenchuan earthquake in China on May 12, 2008, were used for model verification and comparative analysis. Using seismic response analysis theory, 901,530 acceleration records of the Wenchuan earthquake detected by eight actual seismic stations were selected, and nonlinear dynamic time history analysis was conducted. A four-story RC structural model was established using finite element software, and numerical simulation analysis was conducted on the model using 117,863 real earthquake acceleration data points obtained from actual monitoring stations during the Wenchuan earthquake. The acceleration time history curves and incremental dynamic analysis curves of the RC structure under different intensity measures were generated. By combining the moire algorithm and numerical simulation technology, damage stress clouds of steel bars and concrete under different intensity measures were generated, and the accuracy of the developed empirical vulnerability model was verified via numerical simulation results. [ABSTRACT FROM AUTHOR]

East Java is one of the seismically active regions in part of the Sunda Arc whose seismicity pattern must be studied. Therefore, a spatio-temporal analysis of seismicity between 2002 - 2022 in East Java has been conducted. This analysis aims to investigate the seismotectonic conditions in the East Java region over the last twenty years, especially the seismicity patterns associated with significant earthquakes in East Java. The analysis was carried out by quantifying the spatial and temporal variations of seismicity parameters using b-value and z-value. The used data used are earthquake data from the USGS earthquake catalog during 2002 - 2022 in the East Java region. The analysis was performed using the ZMAP 6.0 program code using the maximum likelihood method. The results of the temporal analysis of b-values show that almost all significant earthquakes in East Java were characterized by a decrease in b-values of up to 0.2. Spatially, the significant earthquake on 10 April 2021 was associated with a low b-value (0.9). Temporal z-value analysis shows that the significant East Java earthquake was preceded by a quiet period (positive z-value) between 4 - 5 years (2003 - 2008 and 2012 - 2016). Spatial analysis of the z-value in the last 7 shows an increase in the z-value before the significant earthquakes occurred on 16 July 2019, 18 March 2020, and 10 April 2021. Therefore, the results of this study indicate that the b-value and z-value potentially can be used as precursors of the significant East Java earthquake. [ABSTRACT FROM AUTHOR]

Site amplification factors (SAFs) of seismic ground motions are essential in evaluating and estimating seismic hazards. In our previous study, the authors proposed a simple and cost-effective method to estimate a SAF based on a deep neural network (DNN) model and microtremor horizontal-to-vertical spectral ratio (MHVR). Since the previous DNN model was based on the observed SAFs and MHVRs within a limited district in Japan, the applicability of the previous model to non-source regions with different site conditions was limited. This study explored the application of a transfer learning (TL) technique to adapt an existing (pre-trained) DNN model to new regions and a different database. The SAFs obtained through generalized spectral inversion technique (GIT) at the seismic observation stations (K-NET and KiK-net) in Japan were collated as the ground truth for site effects. MHVRs recorded at the stations in several districts of Japan were collected to construct a data set for the development of the TL model. Subsequently, a TL model was constructed, leveraging the neural network layers and their weights from the pre-trained model while incorporating additional neural network layers to enhance the performance. During the training process, a total data set of 112 sites was divided into training set, validation set, and external test set by 1:1:5. Utilizing a cross-validation strategy, the residuals between pSAFs (pseudo-SAFs) estimated by the TL model and the observed SAFs were analysed for the external test set containing 80 sites. The results showed that the TL model outperformed the pre-trained DNN model. The cross-validation results demonstrated that almost consistent prediction results were obtained regardless of any combination of 16 sites selected as the training set. Furthermore, by contrasting the influence of varying training set sizes on the performance of the TL model and comparing the TL model to a DNN model with an extended training set, the effectiveness of constructing the model with the limited number of data (16 sites) was ascertained. Finally, the effectiveness and limitations of the TL model were evaluated using MHVRs with peak frequencies falling outside the training set's range. [ABSTRACT FROM AUTHOR]

Ensuring the robust performance of damping devices during intense vibrations, such as seismic excitation, is crucial for maintaining structural protection. Hazard analysis serves as an effective method for evaluating the reliability of vibration-damping devices installed on structures subjected to vibrations. This study aimed to conduct a seismic hazard analysis comparing the rotary eddy current damper (R-ECD) and the widely used fluid viscous damper (FVD). To facilitate analysis and engineering applications, this study introduces innovative contributions by proposing a simplified formula for estimating the nonlinear damping force of the R-ECD under specific conditions. This formula incorporates two physically significant parameters: maximum damping force (Fmax) and critical velocity (vcr). By doing so, it offers a swift and efficient tool for the intricate calculation of damping force. The accuracy of this estimation formula is validated by testing a large-scale R-ECD with a maximum damping force exceeding 1,500 kN, revealing a remarkable agreement of ±6.8% between the estimated and experimental results. Subsequently, employing stochastic linearization, the equivalent linear damping ratio of single-degree-of-freedom (SDOF) structures with R-ECD and FVD were derived. Leveraging this stochastic linearization, seismic hazard analysis of these two dampers was carried out. The results indicate that R-ECDs exhibit superior reliability in terms of self-limited output force and their ability to handle large strokes, outperforming FVDs. Moreover, the findings confirm that ECDs are particularly well-suited for long-span structures such as bridges, which are prone to temperature-related influences. [ABSTRACT FROM AUTHOR]

To estimate the connectivity of a road network, it is crucial to evaluate the correlation of hazard intensities among individual bridge locations since the probability of multiple bridges being damaged simultaneously depends on the degree of this correlation. However, research on connectivity assessment of bridge networks considering spatial correlations associated with flood intensities is scarce in the literature. When quantifying the spatial correlation of flood intensities, modeling based on the stream distance rather than the Euclidean distance is required, taking into account that river flow is restricted only within the stream network. To achieve this purpose, a novel methodology is proposed to evaluate the spatial correlation of a stream network based on a geostatistical linear model and stream network covariance models. In addition, this study considers the spatial correlation of seismic hazard intensity. With the proposed method, it is possible to identify which bridges play an important role in ensuring the connectivity of the road network under multiple hazards, i.e. flood and seismic. As an illustrative example, the proposed method is applied to a hypothetical bridge network in Kumamoto Prefecture, Japan. The results demonstrate that improved network connectivity can be achieved by implementing a relevant retrofitting strategy for important bridges. [ABSTRACT FROM AUTHOR]

An updated strong-motion database of the Iranian earthquakes has been used to propose empirical equations for the prediction of peak ground velocity (PGV), peak ground acceleration (PGA), and 5%-damped Spectral Accelerations (SA) up to0.0 s for geometric mean of horizontal components. Some records from the NGA-West2 are added to the database to enrich it at near source distances for large magnitude events. Lack of data in the near source distances causes less accuracy in previous Iranian Ground Motion Models (GMMs) in comparison with the current study. In this work, the regression analyses have been performed on a truncated database which causes to obtain unbiased results. We used 3015 acceleration time series from 594 earthquakes after truncation of data to develop a new GMM. The provided model is valid for Joyner-Boore distances ranging from 0 km to80 km and magnitudes ranging from 4 to 7.9 and Vs30 ranging from50 m/s to500 m/s. [ABSTRACT FROM AUTHOR]

In low to moderate seismic regions such as the Korean peninsula, it is difficult to perform seismic hazard analyses to construct hazard maps and curves because only a limited number of strong ground motion records is available. In this study, to solve such obstacles, ground motions are simulated using a stochastic model for Fourier amplitude spectrum (FAS) in frequency domain and shaping window model in time domain. The generalized inversion technique is adopted to determine the seismological characteristics (source, path, and site effects) of the FAS for Korean region. The validity of the source, path, and site effects obtained from the GIT and that of simulated ground motions is verified. [ABSTRACT FROM AUTHOR]

The Sichuan–Yunnan area is one of the most seismically active regions in China. As ground-motion models form a key component of seismic hazard analysis, it is important to select (or develop) appropriate models for this area. The increasing number of digital ground-motion records of earthquakes in this area has allowed the development of local ground motion prediction equations (GMPEs). This study compares and, later, recommends appropriate GMPEs for the Sichuan–Yunnan area. We first evaluate the inherent quality of local GMPEs, with respect to their underlying datasets, the variables used and their functional forms, to determine a set of candidate GMPEs. Then we investigate how well the predictions from the GMPEs match observations computed from strong-motion records of recent earthquakes in this area. The fit between predictions and observations varies significantly amongst the GMPEs. The results suggest that some recent local GMPEs would lead to biased ground-motion estimates due to limitations of their underlying datasets and functional forms. Based on both evaluations of inherent quality and compatibility with observations, only one local GMPE is recommended. A comparison of the predictions from three widely-used non-local GMPEs indicates that ground motions in the Sichuan–Yunnan area appear more variable than those in other regions but that predictions from these non-local GMPEs are generally unbiased. We recommend use of a mixture of robust local and non-local GMPEs within seismic hazard analyses to capture the epistemic uncertainty in ground-motion prediction for this area. [ABSTRACT FROM AUTHOR]

The track structure has an effect on the dynamic characteristics of the bridge structure, which makes the seismic response of the bridge structure complicated. In this paper, an assessment method is proposed to evaluate the seismic risk of bridge structure, including over-limit risk and over-limit scale. Based on a newly proposed simplified model with high accuracy and high computational efficiency, a total of 3000 calculation conditions are analyzed and the sample stability of response is validated to ensure the reliability of the seismic risk analysis. The seismic risks in the longitudinal direction of the track-bridge model are compared with that of the trackless model, and the influence of the constraint effect of China Railway Track System II ballastless track structure on the seismic risk of the structure is obtained. The influence of the number of spans and PGA on track constraints is also revealed. The analysis results, based on a large number of samples, show that although track constraints can reduce the seismic risk of some phenomenon, such as girders' collision, the expected enhancement of longitudinal seismic safety of the system cannot be guaranteed in general, especially when the number of spans is large. However, it is noted that the track constraint can effectively control the over-limit scale of the system, which can reduce the expected repair cost after an earthquake. Therefore, it can be considered that the positive effect of the track constraints is more significant in economy than in structural safety when the bridge is subjected to a longitudinal earthquake excitation. [ABSTRACT FROM AUTHOR]