Average Shear Wave Velocity Research Articles

Estimation of Vs30 and site classification of Bhaktapur district, Nepal using microtremor array measurement

The severe damage observed in the Kathmandu Basin, Nepal, during past earthquakes necessitates a thorough study of the seismic behavior of the basin sediments. As the shear-wave velocity is directly related to the elastic shear modulus of the material, it is essential to determine it to incorporate the behavior of the soil in the design of the structure. Hence, we determined average shear-wave velocity in upper 30 m (Vs30) of soil in Bhaktapur district in the eastern part of the Kathmandu Basin at 73 observation points, employing two methods involving the use of non-invasive microtremor array measurements (MAMs). These MAMs are widely used for determining subsurface soil characteristics by analyzing the ambient vibrations of the ground. The first method involves inversion using a genetic algorithm, and the second is a method for obtaining Vs30 directly from the dispersion curve. We found that Vs30 in the southeastern part of the study area was higher than that in other parts. Conversely, Vs30 in the western region was lower. The calculated Vs30 values were used to classify the sites. The elevated eastern and southeastern areas with high Vs30 were categorized as dense soil or soft rock, whereas the areas with low Vs30 that had suffered significant damage during the 2015 Gorkha earthquake were classified as soft soil sites.Graphical

INSIGHTS INTO THE MOHO DEPTH VARIATIONS AND CRUSTAL CHARACTERISTICS IN THE GUELMA–CONSTANTINE BASIN, NORTHEASTERN ALGERIA: A SHORT-PERIOD SEISMIC-RECEIVER-FUNCTION PERSPECTIVE

Teleseismic receiver functions (RF) were extracted from data collected at eight short-period, three-component seismic recording stations over the Guelma–Constantine Basin, northeastern Algeria, to improve the understanding of crustal structure and geodynamic processes. The H-κ stacking method was used to determine the Moho depths and average vP/vS ratios at each station. Careful linear inversion of RF was performed to determine the most appropriate average shear-wave and P-wave velocity profiles at each site. Both methods have yielded highly congruent results, with Moho depths showing robust correlations with previous seismological and geophysical studies. The previously observed pattern of the increasing Moho depth from north to south in the Tell Atlas has been confirmed. Furthermore, the identified transitional nature of the Moho in the Constantine Basin is consistent with a recent study. In addition, we identify a low-velocity zone (LVZ) at approximately 20 km depth within the southern Guelma Basin, confirming previous results in the Constantine Basin and suggesting an eastward elongation of the LVZ, at least into the southern periphery of the Guelma Basin. Examination of data from the northern tip of the Hammam Debbagh–Roknia NW–SE fault, the western boundary of the Guelma pull-apart basin, revealed a shallow Moho depth (22 km), less than the basin average depth of 25 km. The LVZ observed in the lower crust (12 km) suggests the presence of partial melts, consistent with gravimetric and chemical analyses of hydrothermal sources in the area. The extensional tectonic activity along this boundary, coupled with the low-viscosity zone and low average vP/vS ratio, is potentially associated with delamination processes. The effectiveness of our approach underscores its potential as a viable alternative or complementary method for investigating variations in the Moho depth.

Ultrasound Shear Wave Elastography of the Arch-Supporting Structures in Symptomatic Flatfoot: A Pilot Study.

The posterior tibial tendon (PTT), deltoid ligament, and spring ligament are often torn or attenuated in patients with progressive collapsing foot deformity. The goal of this pilot study was to measure the ultrasound shear wave velocity (SWV) of these arch-supporting structures in feet with varying degrees of deformity to improve our understanding of their role in the progression of deformity. Two observers measured the SWV of the supramalleolar and inframalleolar PTT in long and short axes, in the tibiospring portion of the deltoid ligament, and in the superomedial band of the spring ligament in 8 neutrally aligned feet, 5 asymptomatic flatfeet, and 7 symptomatic flatfeet. Each measurement was repeated 3 times both with and without an applied eversion stress. Average SWV was lower at all locations in the symptomatic flatfeet compared with normal feet, but these differences were statistically significant only for the inframalleolar PTT and the spring ligament. Externally applied stress led to an increase in the SWV of the ligaments but a paradoxical decrease in the SWV in the supramalleolar PTT. The SWV of the PTT was lower along the short axis compared with the long axis. SWV may be useful in evaluating the severity of degenerative disease of arch-supporting structures, but further study is needed before this technique can be applied clinically. Level III, case-control study.

Dependence of horizontal PGA prediction on site conditions at critically short hypocentral distances: an analysis based on Japanese strong motion data

A fundamental element in seismic hazard assessment studies is the prediction of maximum values of ground accelerations. This is achieved through an attenuation relationship, also known as the ground motion prediction equation (GMPE). Seismic design of structures generally assumes the occurrence of a large earthquake on a nearby fault. The predictions from the GMPE are linked to the magnitude, distance, and local site conditions. Critical near‑fault ground motions have unique characteristics such as magnitude saturation and distance saturation. To investigate the impact of local site conditions in the near‑fault region, we analyzed the attenuation relations using the accelerations recorded in Japan by the Kiban Kyoshin network (KiK‑net) from 2000 to 2023. All events with a magnitude equal to or greater than 5.5, and with focal depth and epicentral distance less than 20 km, were considered. In this study, the hypocentral distance ranges from 5 to 23 km. Ordinary least squares regression analysis was conducted for the maximum horizontal vector of ground accelerations. The attenuation relation coefficients for horizontal vector peak ground acceleration were estimated using an effective distance and saturation effect. An additional independent term, the average shear wave velocity of the soil to a depth of 30 meters below the ground surface, and more cost‑effective shallower depths were included in the regression model. The analysis revealed that the site condition is statistically non‑significant at very short hypocentral distances of less than 23 kilometers.

Generative Adversarial Networks-Based Ground-Motion Model for Crustal Earthquakes in Japan Considering Detailed Site Conditions

ABSTRACT We develop a ground-motion model (GMM) for crustal earthquakes in Japan that can directly model the probability distribution of ground-motion acceleration time histories based on generative adversarial networks (GANs). The proposed model can generate ground motions conditioned on moment magnitude, rupture distance, and detailed site conditions defined by the average shear-wave velocity in the top 5, 10, and 20 m (VS5, VS10, and VS20) and the depth to shear-wave velocities of 1.0 km/s and 1.4 km/s (Z1.0 and Z1.4). We construct the neural networks based on styleGAN2 and introduce a novel neural network architecture to generate ground motions considering the effect of source, path, and such detailed site conditions. The resulting 5% damped spectral acceleration from the proposed GMM is consistent with empirical GMMs in terms of magnitude and distance scaling. The proposed GMM can also generate ground motions accounting for the shear-wave velocity profiles of surface soil with different magnitudes and distances and represent characteristics that are not explained solely byVS30.

A Method for Determining the Fundamental Site Period and the Average Shear Wave Velocity

The soil–structure interaction plays a crucial role in determining the displacement and internal forces of multi-story buildings subjected to strong ground motion. One of the critical dynamic characteristics influencing soil–structure interaction is the fundamental site period and the average shear wave velocity associated with it. This study introduces an original equation to determine these parameters. In addition, for the first time in the literature, the version of the Rayleigh method used for finding the fundamental periods of buildings is used to find the fundamental site period. The soil is modeled as an equivalent shear beam to obtain the proposed equation. The peak displacement is obtained by acting the soil mass as an external load on the equivalent shear beam. For single-layer soil, the fundamental site period is proportional to the square root of the peak displacement of the equivalent shear beam. The least squares method generalizes the proposed relation for single-layer soils to multi-layer soil profiles. Modified Finite element Transfer matrix method is used for calibration in the least squares method. The equations used in the literature and earthquake codes for determining the fundamental site period and average shear velocity are tested on various examples, and it is shown that the method proposed in this study, along with the Rayleigh method, gives better results than these equations. The performances of these two methods and the five commonly used equations are tested and compared on different soil profiles. Transfer functions, Finite Element Method (SAP200) and Modified Finite Element Transfer Matrix Method are used for verification. For all soil profiles, the results obtained from the transfer function, Finite Element Method (SAP200) and Modified Finite Element Transfer Matrix Method are found to be in agreement. The true percent relative error found in the results obtained with the proposed method is 4.47%.

Parametric seismic fragility model for elephant-foot buckling in unanchored steel storage tanks

The parametric seismic fragility model of elephant-foot buckling (EFB) in the tank wall of the unanchored storage tanks is introduced by utilizing the results of a parametric study of eighteen tank-soil configurations. The model can be used to rapidly assess the seismic vulnerability to EFB for a larger number of tanks. The parametric study involved a 1D cloud-based soil response analysis to relate the ground-motion intensity measure at the bedrock with that at the free surface, and a pushover analysis of the refined finite element model of the tank to assess the engineering demand parameter in terms of axial compressive stress in the tank wall and the critical value that triggers EFB. As a consequence, the parametric seismic fragility model can be applied to intensity measures at the bedrock, as it is demonstrated for the spectral acceleration at the tank’s impulsive period, Se,bedrock,EFB, and the peak ground acceleration, PGAbedrock,EFB. The input parameters of the introduced seismic fragility model are the harmonic average shear-wave velocity in the top 30 m of soil, Vs,30, the slenderness ratio of the tank, H/R, the ratio between radius and wall thickness of the tank, R/t, and the standard deviation of log values for the intensity measure causing EFB. The model reliably predicts the median intensity measure causing the onset of EFB in the investigated tank-soil configurations, especially when Se,bedrock,EFB is selected for the intensity measure. However, further investigation is required to enhance the accuracy of predicted intensity measures that trigger EFB by considering the dynamic impact between the base plate and the foundation during an earthquake and accounting for the complete soil-structure interaction effects.

An earthquake spectra parameters near the new capital administrative city, Egypt

Seven Strong Motion stations recorded an earthquake of Mw 3.8 on December, 31 2018 on the Cairo- Suez southern road. The furthest NUB station is about 302 km from the epicenter, whereas the closest KOT station is 10 km away. This event is considered the first recorded acceleration event near the new capital administrative city. The KOT station has the highest recorded acceleration, measuring 16.38 Gal. The peak ground velocity (PGV), peak ground displacement (PGD), and Pseudo acceleration values for the same station are calculated to be 0.00109 m/s, 0.114 cm, and 0.0731 g, respectively. An intensity map was created for this event as a questionnaire gathered information from Facebook and EMSC. In the vicinity of Qattamiya Observatory, the maximum observed intensity is (IV). According to the geological information and average shear wave velocity calculated from previous studies, We classified the station sites into soil types B, C, and D. We correlated them with the HVSR analysis obtained from S-wave earthquake data. The maximum amplification factor (A0) was found for a BANH station equal to 5.8 and equivalent to the Fundamental frequency (F0) of 3 Hz. The minimum amplification factor was found to be for stations of ISM & NUB with A0 equal to 2.8 and 1.6, respectively, while Fundamental frequency (F0) was 0.7 and 2 Hz, respectively. At the KOT station, the response design spectrum indicates a maximum value of 70 Gal. The new Egyptian capital administrative city is strongly advised to set up an early warning system and structural earth monitoring to manage the risk assessment of any potential seismic activities in the future.

Prediction of local site influence on seismic vulnerability using machine learning: A study of the 6 February 2023 Türkiye earthquakes

This study uses machine learning to analyze local seismic features' influence on damage from the 6 February 2023 Türkiye Earthquakes.The input features include Vs30 (the average shear wave velocity to a depth of 30 m), f0 (the predominant frequency of the site), A0 (HVSR ratio for the site), and EBd (engineering bedrock depth), along with the target feature of damage status for 44 locations. Machine learning involves Random Forest (RF), K-nearest Neighbor (KNN), Logistic Regression (LR), Decision Trees (DT), Support Vector Machines (SVM), Stochastic Gradient Descent (SGD), and Multilayer Perceptron (MP) algorithms. Also, five-fold cross-validation is employed to acquire suitable hyperparameters, enhancing its efficacy in modeling small sample sets. RF emerged as the most effective in whole performance metrics, presenting recall scores for damage and no damage conditions respectively by a 94% and 92% ratio and achieving a damage status prediction accuracy of 93%. All remaining algorithms also exhibited remarkable performance, reaching a minimum accuracy of 89% by DT, and recall score for no damage condition with 80% by MP and damage condition with 88% by SVM and SGD. The outcomes definitively designate EBd as the most crucial parameter, attributing 52% importance to its role in building damage occurrence within the study area. In contrast, significance values were determined as 24%, 18%, and 6% for f0, Vs30 and A0 respectively. These findings underscore the importance of demonstrating that initial damage estimation in high seismic hazard zones can be effectively carried out using machine learning approaches through seismic-based local site parameters.

Site-specific probabilistic seismic hazard analysis in Nuweiba, Gulf of Aqaba, Egypt: Combining area source model and active faults

Gulf of Aqaba in Eastern Egypt is characterized by significant seismic activity and high deformation rate, making it a major source of destructive earthquakes in the region. While previous studies have produced probabilistic seismic hazard analysis (PSHA) maps for the region, they have not adequately accounted for active faults or site response in their calculations. This study introduces a newly developed seismic source model for the Gulf of Aqaba, considering area source, active fault source, and a combination of both models to improve seismic hazard assessment for the region. The study incorporates the previously measured average shear-wave velocity for the upper 30 m (Vs30), fundamental frequency (F0), and amplification factor (A0) at some selected sites in Nuweiba city. Accordingly, site-specific PSHA is carried out for the bedrock condition (Vs30 = 800 m/s, according to the Egyptian Building Code) and for the surface of soft sediments using F0, A0, and Vs30. Uncertainties in slip rate, maximum magnitude, and recurrence model are accounted during PSHA computation. Ground motion parameters such as peak ground acceleration (PGA) and spectral acceleration (SA) for various probabilities of exceedance in 50-year lifetime are calculated for both rock site conditions and soft sediments. The maximum calculated PGA and SA are 0.65 g and 1.25 g, respectively, for a 10% probability of exceedance over 50 years at bedrock conditions.

Nonlinear seismic response analysis of slopes considering the coupled effect of slope geometry and soil stratigraphy

SUMMARY To investigate the effects of slope geometric parameters and soil stratigraphic properties on the topographic amplification of ground motions, a large number of 2-D horizontally layered slope models are constructed. First, the linear and nonlinear seismic responses of a slope model are compared, and the result shows that the nonlinear characteristics of soils should be considered when studying the amplifying effect of slope topography on ground motions. Then, the nonlinear seismic responses of these slope models are analysed from four aspects: the maximum shear strain in the slopes, the effects of geometry and stratigraphy on the seismic response, the distance between the maximum topographic amplification indicators and the slope crest, and the influence range of slope topography behind the slope crest. The results indicate that the amplifying effect of slope topography on ground motions increases with increasing slope height or decreasing average shear wave velocity of the overlying soil layers. Besides, the variation of the topographic amplification effect with slope gradient is significantly influenced by soil stratigraphic properties. The distance between the maximum topographic amplification indicators and the slope crest is mainly in the range of 0–60 m, and the influence range of slope topography behind the slope crest is mainly in the range of 0–150 m. Subsequently, approximate relations are derived based on regression analyses of simulation results, which can provide meaningful references for the seismic design and seismic retrofitting of engineering structures behind the slope crest. Finally, the effects of slope geometric parameters and soil stratigraphic properties on ground motion modifications are further evaluated according to the prediction curves provided by the approximate relations.

Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models

Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m ( VS30) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.

Physico-mechanical Properties Estimation of Upper Siwalik Sandstone using Field (MASW) and Laboratory Test, Himachal Himalaya, India

Abstract A study on the Upper Siwalik Sandstone was conducted to determine and compare the relationship between shear wave velocity and the petro-physical and petro-mechanical characteristics of the sandstone. Two localities in the Himachal Himalaya’s Bilaspur district were sampled for collection of sandstone of Upper Siwalik. The method of Multichannel Analysis of Surface Waves (MASW) was used to obtain average shear wave velocity at 30m depth (Vs30) in the field. The shear modulus of rocks is intimately correlated with the Vs30 parameter. The Vs30 value is 185 m/s for the Majher Khad (sandstone A) region and 366 m/s for the Dharot region (sandstone B). Based on obtained Vs30 values these two regions are classified under class D and class C respectively by the National Earthquake Hazards Reduction Program (NEHRP). Both the rocks belong to Upper Siwalik Sandstone, but diversity in Vs30 and shear modulus values can be ascribed to the composition of minerals, the size of the grains, and the cementing substances present in the rock.

Significant duration prediction of seismic ground motions using machine learning algorithms.

This study aims to predict the significant duration (D5-75, D5-95) of seismic motion by employing machine learning algorithms. Based on three parameters (moment magnitude, fault distance, and average shear wave velocity), two additional parameters(fault top depth and epicenter mechanism parameters) were introduced in this study. The XGBoost algorithm is utilized for characteristic parameter optimization analysis to obtain the optimal combination of four parameters. We compare the prediction results of four machine learning algorithms (random forest, XGBoost, BP neural network, and SVM) and develop a new method of significant duration prediction by constructing two fusion models (stacking and weighted averaging). The fusion model demonstrates an improvement in prediction accuracy and generalization ability of the significant duration when compared to single algorithm models based on evaluation indicators and residual values. The accuracy and rationality of the fusion model are validated through comparison with existing research.

Liver Elastography in Acute Liver Failure: A Pilot Study.

We aimed to assess the feasibility and reliability of sequential ultrasonographic and elastographic monitoring in acute liver failure (ALF). Observational study. ALF is a rare, life-threatening disease that requires intensive care admission and often liver transplant, where the accurate selection of patients is crucial. Liver elastography is a noninvasive tool that can measure hepatic stiffness, but previous results have been inconclusive in ALF. Patients admitted between October 2021 and March 2023 to the Liver Intensive Therapy Unit at King's College Hospital with ALF were recruited, with healthy control (HC) individuals and acute-on-chronic liver failure (ACLF) used as controls. None. Average shear wave velocity was recorded with ElastPQ on the right and left liver lobes and the spleen. Portal vein flow, hepatic artery resistive index, and peak systolic velocity were also recorded. Physiologic and histologic data were used for comparison. Forty patients with ALF, 22 patients with ACLF, and 9 HC individuals were included in the study. At admission, liver stiffness measurement (LSM) of the right lobe was statistically different between HC individuals (5.6 ± 2 kPa), ALF (31.7 ± 17 kPa), and ACLF (76.3 ± 71 kPa) patients (ALF vs. ACLF, p = 0.0301). Spleen size and stiffness discriminated between ALF (10.4 ± 2 cm and 21.4 ± 16.6 kPa) and ACLF (14 ± 2.3 cm and 42.6 ± 26 kPa). At admission, LSM was not different between ALF patients who spontaneously survived versus patients who died or were transplanted in the following 90 days. However, the trend over the first 10 days of admission was different with a peak of LSM at day 5 in spontaneous survivors followed by reduction during the recovery phase. ALF patients with poor prognosis showed a persistently increased LSM. In ALF stiffness peaks at day 5 of admission with subsequent reduction in patients spontaneously surviving, showing significant difference according to the prognosis at day 7 of admission. LSM might be useful in distinguishing acute from acute-on-chronic liver failure together with spleen volume and stiffness.

Implications of the 2020 National Building Code of Canada updates on the design demands for reinforced concrete shear wall buildings

The seismic demands of the Reinforced Concrete Shear Walls (RCSWs) system are determined based on Canada’s National Building Code (NBC). NBC 2020 features the revised Canadian Seismic Hazard Model and presents the possibility of enhancing demand’s accuracy by determining design spectra based on the specific average shear wave velocity, instead of specified site classes. This paper investigates the changes in design demands for RCSWs compared to the previous edition. To do so, fifty-five RCSW prototypes were modelled using distributed mass and stiffness procedure, and their dynamic response was assessed through Modal Response Spectrum Analysis at five locations across Canada. The results highlight significant changes in deformation and force demands, where the majority of cases experienced an increase in 2020 compared to 2015 when demands were determined based on specified site classes. This study also evaluates the log-log interpolation method recommended by NBC 2020 for the design spectral acceleration.

Geospatial liquefaction probability models based on sand boils occurred during the 2017 M5.5 Pohang, South Korea, earthquake

The 2017 Pohang earthquake, triggered by an enhanced geothermal system, had a moment magnitude (M) of 5.5 and caused liquefaction in Pohang City, South Korea. Notably, approximately 600 sand boils were observed only in the soft Quaternary alluvial sediments. This contrasts with most historic liquefaction cases that occurred in earthquakes with M ≥ 6.0. In addition, ground and building settlements were reported in Pohang City. To assess the liquefaction hazard for the Pohang earthquake within the city, we define a 14.4 km2 area where the majority of liquefaction was observed. Using the liquefaction data, we develop eight geospatial liquefaction probability models using logistic regression (LR) and random forest (RF) algorithms (five LR- and three RF-based models). These models consider geospatial data (peak ground acceleration, peak ground velocity, slope-derived average shear wave velocity of the upper 30 m, compound topographic index, distance to the nearest water, and roughness) and geotechnical data (averaged standard penetration test N values up to 20 m depth, depth to rock). We evaluate the performances of our eight models and existing global and regional geospatial models using four indicators: accuracy, balanced accuracy, F1 score, and area under the receiver operating characteristic curve. The three RF-based models outperform the other models, followed by the best LR-based model and the global geospatial model from Zhu et al. (2015). Finally, we apply the best RF-based model to the entire Pohang City and evaluate its applicability to other regions and earthquakes. The estimated liquefaction probabilities agree well with the observed distributions of the sand boils and settlements. These geospatial liquefaction models provide a valuable tool for continuously mapping liquefaction hazards in areas with similar geological and geotechnical conditions to Pohang.

Optimizing Terrain Classification Methods for the Determination of Bedrock Depth and the Average Shear Wave Velocity of Soil

The advancement of remote sensing has enabled the creation of high-resolution Digital Elevation Models (DEMs). Topographic features such as slope gradient (SG), local convexity (LC), and surface texture (ST), derived from DEMs, are related to subsurface geological conditions. In South Korea, bedrock depth (Dbedrock) and the average shear wave velocity of soil (VSsoil) serve as metrics for determining the site class, which represents the degree of site amplification in seismic design criteria. These metrics, typically measured through geotechnical and geophysical investigations, require predictive methods for preliminary estimation over large areas. Previous studies developed an automatic terrain classification (AC) scheme using SG, LC, and ST, and subsequent research revealed that terrain classification effectively represents subsurface conditions such as Dbedrcok and average shear wave velocity down to 30 m depth. However, AC intrinsically depends on the regional features of DEMs, dividing regions based on nested means of topographic features (SG, LC, and ST). In this study, we developed two terrain classification methods to determine the thresholds of class divisions, aiming to optimize Dbedrock and VSsoil predictions: Sequentially Optimized Classification (SOC) and Non-Sequentially Optimized Classification (NOC). Through the study of the sensitivity of terrain classification methods, smoothing levels, and threshold levels for terrain class generation, we identified the best classification method by comparing it with the geological and mountainous region distribution. Subsequently, we developed DEM-dependent regression models for each class to enhance the accuracy of predicting Dbedrock and VSsoil. The main findings of this study are: (1) the terrain class map suggested in this study represents the distribution of alluvial plane and mountainous regions well, and (2) the DEM calibration for each class provides increased accuracy of Dbedrock and VSsoil predictions in South Korea. We anticipate that the terrain class map, along with Dbedrock and VSsoil maps, will be effectively utilized in geological interpretations and land-use planning for seismic design.

Development of Nonlinear Site Amplification Model Based on Average Shear-wave Velocity of Soil Layer and Bedrock Depth

Development of Nonlinear Site Amplification Model Based on Average Shear-wave Velocity of Soil Layer and Bedrock Depth

Investigation of Ambient Seismic Noise in Different Region of Georgia

Georgia, like the whole South Caucasus, is a tectonically and structurally complex region. It is one of the active segments of the Alpine-Himalayan belt, therefore it is important to assess the seismic hazard for Georgia. At the regional scale, this assessment is evaluated by applying probabilistic seismic hazard analysis that identifies the annual probability of exceedance of various ground motion levels defined in terms of selected ground motion intensity measures, such as PGA or spectral accelerations (SA) corresponding to various return periods related to possible future earthquake scenarios for a site represented by soil classes A according to EC8, Euro-code 8-EN 1998-1 (1998). At the local scale, seismic hazard assessment is made by analyzing the geological, geomorphological, geotechnical and geophysical characteristics of the site, as it is well established that the incoming seismic motion can change in amplitude, frequency, and duration due the site-specific local characteristics. That is the subject of micro-zonation investigation. Site – specific local characteristics are presented by the following parameters: Dominant frequency, Vs,30 (average shear-wave velocity to a depth of 30 meters) and amplification factor. In this work, we presented results of geophysical survey assessing local site conditions by dominant frequency that allows identification of similar seismic response areas. For this purpose, seismic noise records have been used first time in Georgia.