Pseudo-spectral Acceleration Research Articles

Ground-motion model for Housner’s spectrum intensity based on a novel hybrid-scenario approach

We use a novel hybrid-scenario approach to develop a ground-motion model (GMM) for Housner’s spectrum intensity ( SI) using estimates of pseudo-spectral acceleration ( PSA) from the authors existing GMMs based on a scenario approach proposed in the literature and predictor variables from the same database used to develop the PSA GMMs. These estimates of SI are used together with the predictor variables to develop a hybrid-scenario GMM using mixed-effects regression analysis. Because the GMM is based on predicted values of PSA, the aleatory variability from the regression is not indicative of the actual variability of observed values of SI. Instead, a hybrid-scenario model for magnitude-dependent between-event, within-event, and total aleatory standard deviations is derived from the PSA GMMs using the scenario approach. The predicted values of SI and its standard deviations from the hybrid-scenario model are found to be relatively consistent with the residuals between these predictions and estimates of SI from the database (i.e. the observations). However, the values of SI predicted from a purely empirical GMM developed directly from the observations are different than those from the hybrid-scenario model by up to a few tens of percent. These differences are the result of an insufficient number of observations resulting from bandwidth limitations of the database that lead to a bias in the empirical results. The near-source standard deviations from the hybrid-scenario GMM are found to be generally consistent with both those from the empirical model and those from the residuals between the hybrid-scenario model and the observations. However, the far-source standard deviations of the hybrid-scenario model are smaller than those from these other methods.

Stochastic Ground-Motion Simulation of the 2021 Mw 5.9 Woods Point Earthquake: Facilitating Local Probabilistic Seismic Hazard Analysis in Australia

ABSTRACT The 2021 Mw 5.9 Woods Point event is the largest onshore earthquake that has occurred in the recorded history of southeastern Australia since European settlement. To study its source and ground-motion characteristics and to extract information for local seismic hazard analysis, we employ a stochastic finite-fault simulation approach to simulate ground motions for this event based on the observations collected from 36 onshore stations. We determine the regional distance-dependent attenuation parameters using the horizontal Fourier acceleration amplitude spectrum in the frequency range of 0.1–20 Hz. We parameterize path parameters using different models to consider uncertainties and sensitivities. To investigate local site effects, we construct a VS30-based site amplification model. Source parameters are then determined by fitting the theoretical Brune’s ω2 model with a reference Fourier source spectrum at 1.0 km. The κ0 value for the reference rock site is estimated as κ0=0.01 s, and dynamic stress drop is found to be 41.0 MPa by minimizing the overall absolute residual of 5% damped pseudospectral acceleration. We validate the simulations by comparing simulated and observed ground motions in terms of various intensity measurements; analyses of residuals show that the simulations are in good agreement with observations (average residual is close to 0). To facilitate future probabilistic seismic hazard analysis, six selected ground-motion models are ranked using the deviance information criteria based on an independent data set consisting of field observations and simulated ground motions.

On the seismic response and earthquake-triggered failures of subaqueous slopes in Swiss lakes

SUMMARY Seismically triggered subaqueous mass movements in lakes may generate tsunamis that can cause significant damage on the shore. In this study, we assess the seismic response and stability of subaqueous slopes in Swiss lakes based on recorded seismological data, historical and geological information and geotechnical surveys. We performed seismic investigations at multiple locations in Lake Lucerne using Ocean Bottom Seismometers (OBS). For these locations, we derived ground-motion amplification functions from local and regional earthquakes and horizontal-to-vertical spectral ratios (H/V) from the earthquake and ambient vibration recordings. The results show (1) very high amplification levels, often exceeding values of 50–100 in the frequency range between 1 and 10 Hz, (2) the fundamental frequency of resonance in the range of 0.5–3.5 Hz and (3) laterally variable site response even for closely located stations. We sought also the signatures of non-linear site response in the H/V curves or ground-motion amplification functions but found only weak indicative effects and no clear evidence. This is most likely due to the low levels of ground motion recorded during the OBS campaigns. We conducted back analyses of historical earthquakes in Switzerland with available documental and/or geological evidence of induced (tsunamigenic) subaqueous slope failures in Swiss lakes. The data set of historical events was complemented with a selection of instrumentally recorded earthquakes in Switzerland. For the analyses, we selected multiple sites in Swiss lakes which failed in the past or are prone to failure in the future. We modelled the ground motion at these locations assuming Swiss standard reference rock conditions (vs30 = 1105 m s−1). The modelled ground motion intensity measures (IM) included peak ground acceleration (PGA), peak ground velocity (PGV) and pseudospectral acceleration (PSA) at 0.3, 1 and 2 s. We estimated the minimum ground motion and macroseismic intensity at reference rock conditions required to trigger the failures of subaqueous slopes. In addition, we defined a threshold for the seismic triggering of such failures in terms of moment magnitude (Mw) and epicentral distance (Re) as: $$\begin{eqnarray} M_{\rm w}=2.891+1.904\log_{10}(R_e+5.166)\: {\rm for}\: R_e\ge 3.7\: {\rm km}. \end{eqnarray}$$ Our results are consistent with previous studies based on worldwide observations. Furthermore, we related the modelled ground motions to the Swiss seismic hazard products and estimated the return period of critical ground shaking responsible for triggering subaqueous slope failures (with potential for tsunami generation) to be in the range of 36–224 yr. Finally, based on previously collected geotechnical data (in situ Cone Penetration Testing and laboratory sediment analysis), we determined the most likely values of the seismic coefficient k to be used with the ground motion IMs modelled at reference rock conditions in infinite slope stability analyses to estimate the factor of safety (FS). For PGA, we found a k = 1; for PGV, k = 2; for PSA0.3s, k = 0.6; for PSA1s, k = 2 and for PSA2s, k = 5.5. These estimates are conservative and affected by the trade-off between the thickness of unconsolidated sediments and the slope angle. Thus, we recommend applying them to slopes with a low-to-moderate gradient (<15°) and sediment thickness of more than 2 m.

Next generation ground-motion prediction equations for Indo-Gangetic Plains, India

Seismic hazard analysis (SHA) of Indo-Gangetic Plains (IGP), India, and its proximity to the Himalayas requires reliable ground motion prediction equations (GMPEs). This study attempts to derive the GMPEs for IGP using strong-motion accelerometer data recorded from 2005 to 2015 on IGP. For regression, peak ground acceleration (PGA) and pseudo-spectral acceleration (PSA) of 5% damped linear pseudo-absolute acceleration response spectra at 27 periods ranging from 0.01–10 s were used. Two-stage nonlinear regression trains the functional form of nonlinear magnitude scaling, distance scaling, and site conditions. The model includes a regionally independent geometric attenuation finite fault distance metric, style of faulting, shallow site response, basin response, hanging wall effect, hypocentre depth, regionally dependent anelastic attenuation, site conditions, and magnitude-dependent aleatory variability. Developed GMPEs are validated for active crustal continental earthquakes for epicentral distances REPI ranging from 10–1500 km, magnitude ranging from 3.3–7.9, and focal depths 1–70 km. The GMPEs developed are compared with the Campbell and Bozorgnia 2008, 2013 and 2014, and North Indian GMPEs, which are agreed upon consistently. The model can predict the horizontal ground motion for SHA on IGP, considering possible maximum magnitude earthquakes from the seismic gaps of the Himalayas.

The potential of region-specific machine-learning-based ground motion models: Application to Turkey

Conventional ground motion models have extensively been established worldwide based on classical regression analysis of records. Alternatively, advanced nonparametric machine-learning (ML) algorithms may capture the complex nonlinear behaviour of earthquake motions. This paper investigates the efficiency of artificial neural network (ANN) and extreme gradient boosting (XGBoost) in predicting peak ground acceleration (PGA), peak ground velocity (PGV) and pseudo-spectral acceleration (PSA) (period, T = 0.03–2.0 s) for the Turkish dataset. The dataset involves 1166 records of 383 events with a moment magnitude (Mw) of 4.0–7.6, Joyner and Boore distance (RJB) of 0–200 km, focal depth (FD) less than 35 km, and site condition as the averaged shear wave velocity of the soil on the top 30 m (VS30) of 131–1380 m/s. The performance of the models is compared against empirical models in terms of root-mean-square error (RMSE), coefficient of determination (R2), Pearson correlation coefficient (r), and inter-event and intra-event residuals. To perform residual analysis, a likelihood function is developed. Findings reveal that the XGBoost approach gives an unbiased model with a higher correlation and lower residual than ANN. Finally, an online platform is provided for any interested users.

A non-ergodic spectral acceleration ground motion model for California developed with random vibration theory

A new approach for creating a non-ergodic pseudo-spectral acceleration (PSA) ground-motion model (GMM) is presented, which accounts for the magnitude dependence of the non-ergodic effects. In this approach, the average PSA scaling is controlled by an ergodic PSA GMM, and the non-ergodic effects are captured with non-ergodic PSA factors, which are the adjustment that needs to be applied to an ergodic PSA GMM to incorporate the non-ergodic effects. The non-ergodic PSA factors are based on the effective amplitude spectrum (EAS) non-ergodic effects and are converted to PSA through Random Vibration Theory (RVT). The advantage of this approach is that it better captures the non-ergodic source, path, and site effects through small-magnitude earthquakes. Due to the linear properties of the Fourier Transform, the EAS non-ergodic effects of the small events can be applied directly to the large magnitude events. This is not the case for PSA, as response spectra are controlled by a range of frequencies, making PSA non-ergodic effects dependent on the spectral shape, which in turn is magnitude-dependent. Two PSA non-ergodic GMMs are derived using the ASK14 (Abrahamson et al. in Earthq Spectra 30:1025–1055, 2014) and CY14 (Chiou and Youngs in Earthq Spectra 30:1117–1153, 2014) GMMs as backbone models, respectively. The non-ergodic EAS effects are estimated with the LAK21 (Lavrentiadis et al. in Bull Earthq Eng ) GMM. The RVT calculations are performed with the V75 (Vanmarcke in ASCE Mech Eng Mech Division 98:425–446, 1972) peak factor model, the D_{a0.05-0.85} estimate of AS96 (Abrahamson and Silva in Apendix A: empirical ground motion models, description and validation of the stochastic ground motion model. Tech. rep.,. Brookhaven National Laboratory, New York) for the ground-motion duration, and BT15 (Boore and Thompson in Bull Seismol Soc Am 105:1029–1041, 2015) oscillator-duration model. The California subset of the NGAWest2 database (Ancheta et al. in Earthq Spectra 30:989–1005, 2014) is used to fit both models. The total aleatory standard deviation of each of the two non-ergodic PSA GMMs is approximately 25% smaller than the total aleatory standard deviation of the corresponding ergodic PSA GMMs. This reduction has a significant impact on hazard calculations at large return periods. In remote areas, far from stations and past events, the reduction of aleatory variability is accompanied by an increase in epistemic uncertainty.

Impact of ground-motion duration on nonlinear structural performance: Part I: spectrally equivalent records and inelastic single-degree-of-freedom systems

In current seismic performance-based assessment approaches, nonlinear dynamic analysis of structures generally relies on ground motions selected based on their pseudo-spectral accelerations, with little or no consideration for ground-motion duration. Part I of this study, presented in this article, attempts to comprehensively quantify the impact of ground-motion duration on the nonlinear structural performance of case-study inelastic single-degree-of-freedom systems for shallow-crustal seismicity conditions. The effect of duration is decoupled from that of ground-motion amplitude and spectral shape by assembling sets of spectrally equivalent long- and short-duration records. Such sets are employed in incremental dynamic analyses of a wide range of computational models incorporating in-cycle and cyclic strength and stiffness deterioration. The structural response is quantified in terms of peak- and cumulative-based engineering demand parameters. Formal hypothesis testing is used to assess the statistical significance of duration’s impact on the median structural capacity of the considered structural systems. Furthermore, the derivation of duration-dependent fragility and vulnerability relationships demonstrates that ground-motion duration effectively impacts the nonlinear structural performance of various systems, and it should be accounted for in current practice. The fragility median values for highly deteriorating structural systems under long-duration ground motions are found to be up to 21% or 34.0% smaller than the short-duration counterpart if a peak- or cumulative-based engineering demand parameter is adopted, respectively.

Impact of ground-motion duration on nonlinear structural performance: Part II: site- and building-specific analysis

This study’s Part I proved that ground-motion duration could play an important role when assessing the nonlinear structural performance of case-study inelastic single degree-of-freedom systems. However, quantifying duration effects in many practical/more realistic engineering applications is not trivial, given the difficulties in decoupling duration from other ground-motion characteristics. This study’s Part II, introduced in this article, explores the impact of duration on nonlinear structural performance by numerically simulating the structural response of realistic case-study reinforced concrete bare and infilled building frames. Advanced computational models incorporating structural components’ cyclic and in-cycle strength and stiffness deterioration, and destabilizing [Formula: see text] effects are used. The proposed methodology relies on the generalized conditional intensity measure approach to select ground motions. This allows selecting records consistent with the seismic hazard at a target site, both in terms of spectral shape and duration. Those are employed as input to cloud-based nonlinear structural response analyses. Variance analysis is used to quantify the impact of duration on structural response. Furthermore, vector-valued fragility and vulnerability models alternatively using peak- and cumulative-based engineering demand parameters are derived. Results show that higher damage/loss estimates can be attained as ground-motion duration increases. Relative differences up to 44% are found in fragility median values for a pre-code reinforced concrete infilled frame when comparing scalar and vector-valued fragility models conditioned on average pseudo-spectral acceleration and significant durations up to 35 s.

A hybrid non‐parametric ground motion model for shallow crustal earthquakes in Europe

AbstractIn the current study, ground motion models (GMMs) are derived using the European Strong Motion (ESM) database for pseudo‐spectral acceleration (PSA), peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement (PGD), cumulative absolute velocity (CAV), arias intensity (Ia), and significant duration. In addition to addressing random effects associated with ground motion regression, such as inter‐event, inter‐site, inter‐locality, and inter‐region variabilities, the current study also aims at reducing the standard deviations (STDs) of the GMMs through development of a hybrid non‐parametric GMM. The hybrid model is derived through an ensemble‐weighted method of five non‐parametric machine learning models: shallow neural network, deep neural network (DNN), gated recurrent unit (GRU), support vector, and random forest (RF) regression techniques; with weights based on model performances. The resulting hybrid model, which also accounts for epistemic uncertainty, is compared against other regional models and is found superior for all output variables. The inter‐event, inter‐site, inter‐locality, and inter‐region deviations, and total ergodic sigma of PSA for the ensemble model lies between 0.3164–0.4478, 0.4156–0.5339, 0.1449–0.3687, 0.0819–0.2421, and 0.668–0.8545, respectively. The coefficient of determination (R2) between predicted and recorded values lies between 0.8435–0.9114 for all the output variables.

Including Radiation-Pattern Effects in Ground-Motion Models for Taiwan

ABSTRACT Most ground-motion models (GMMs) parameterize the earthquake source by magnitude, style of faulting, and source depth. GMMs are isotropic in terms of the source scaling for these three parameters. The radiation pattern, which leads to azimuthally varying source effects, is not included in most GMMs. As a result, any systematic radiation-pattern effects are treated as aleatory variability in the path terms in the GMMs, which does not make physical sense. We incorporate the far-field radiation pattern into GMMs for pseudospectral acceleration and Fourier amplitude spectra for the Taiwan region. A key issue is how to combine the radiation pattern from the SH and SV components for predicting the RotD50 amplitudes of ground motions used in GMMs. A suite of point-source simulations was generated for a range of focal mechanisms and site azimuths. Empirical models for the phase differences between the radial and transverse components were developed to constrain the between-component phase differences in simulations. The results show that the vector sum of the SH and SV far-field radiation patterns, FS, has a higher correlation with the RotD50 amplitudes of the ground motion than the arithmetic mean or the geometric mean. The radiation-pattern term is modeled by S0(M)+S1(M)ln(Fs+S2), in which S0(M) and S1(M) are linear functions of magnitude between M 4 and 6; they equal 0 for M > 6. The magnitude dependence reflects that, for large magnitudes and short distances, ground motions are more affected by the slip distribution and rupture timing than by the average radiation pattern from the subevents along the rupture, but the radiation pattern has a significant effect on the long-period ground-motion amplitude for small-magnitude events. Including radiation patterns into GMMs will improve estimates of 3D path effects from small-magnitude events by removing radiation-pattern effects from combined radiation-pattern and path terms used in current GMMs.

A far-field ground motion prediction model for interface earthquakes at the hill zone of Mexico City

This study presents an updated attenuation model to predict the peak ground acceleration (PGA), peak ground velocity (PGV), 5% damped pseudo-spectral acceleration (SA), and the average spectral acceleration (AvgSA) at the hill zone of Mexico City for interface earthquakes. The strong-motion dataset comprises 33 earthquakes recorded at CU station, covering a moment magnitude (Mw) range from 6.0 to 8.1 and a source-to-site distance (Rrup) range from 240 to 490 km. Given the small number of available observations, a Bayesian regression scheme is used to obtain the coefficients of the ground-motion prediction model (GMPM). In addition, the epistemic uncertainty in the estimation of the regression coefficients is evaluated, showing its impact on the framework of a probabilistic seismic hazard analysis (PSHA). The results are compared with models previously developed for the CU station, discussing the differences observed between the median predictions and their standard deviations. Likewise, seismic hazard curves are computed and compared with empirical curves obtained by counting the number of times per year that a given value of ground-motion intensity is exceeded. The results show that the dispersion of the GMPM proposed is lower than the previous models for PGA and SA, which means better predictability and more reliable estimates of the seismic hazard at the site.

Ground motion model for Peninsular India using an artificial neural network

Ground motion models (GMMs) are an essential tool for seismic hazard analysis. They are used for developing predictive relationships to estimate the expected levels of seismic ground shaking through the ground motion parameters (GMPs). There is limited recorded data on the stable continental regions (SCR) such as Peninsular India (PI), and Central and North Eastern America (CENA), and GMMs are developed either by hybrid or stochastic methods. In this study, an effort has been made to develop a GMM for the PI region by compiling the recorded data from the CENA and PI regions, as well as from the Near Source Strong (NESS) data. An artificial neural network coupled with the genetic algorithm is considered to develop GMMs. So, the GMP-1 model is developed for various GMPs for both RotD50 and vertical components, while the GMP-2 model is developed for RotD50 components of peak ground acceleration (PGA), peak ground velocity (PGV), and the 5% damped pseudo-spectral acceleration (PSA) for periods between 0.01 and 3 s. The developed models are valid for magnitudes between 2–7.7 Mw and 0 to 1500 km Joyner–Boore distance. In addition, a parametric study is performed with the developed models for various combinations of predictor variables, and it is noticed that both the models capture the trend and attenuation pattern observed in the recorded data for all the GMPs. Moreover, the GMP-2 model predictions agree well with the recorded data compared with the candidate GMMs developed in the NGA-EAST project. A comparison of the GMP-2 models with the recorded data in the PI region indicates the robustness and effectiveness of the developed model in providing reasonable estimates of GMPs, implying its applicability to tectonic environments similar to the CENA region.

Using a grid-search approach to validate the Graves–Pitarka broadband simulation method

This work assesses the ability of the Graves–Pitarka simulation approach to reproduce observed ground motions for 12 California and Baja California earthquakes. A total of 240 realizations are computed for each earthquake and compared with recorded strong motions from near-fault sites. In addition to spatial variability in slip, each realization samples from discrete combinations of average rupture speed, rise time, and down-dip fault width. Ground motions for each realization of a given earthquake are compared to the observations using a pseudo-spectral acceleration goodness-of-fit (GoF) metric. Parameters for the lowest misfit cases are then tabulated to develop relations for estimating median values and ranges for future applications. The results are generally consistent with published scaling relations for estimating rupture dimensions as a function of magnitude. Additionally, I find the average rise time scales as {2.3times alpha }_{T}times {10}^{-9}{times M}_{o}^{1/3} (Mo is seismic moment in dyne-cm) and average rupture speed as (0.765 pm 0.075)times {alpha }_{T}^{-1}times {V}_{s} (Vs is local shear wave velocity), where aT is a mechanism adjustment ranging from a value of 1.0 for pure strike-slip to 0.9 for pure reverse-slip cases. There are cases where slightly different combinations of parameters produce equally good fits to the observations, demonstrating the non-uniqueness of using a single GoF metric in this approach. Nonetheless, the results reinforce the importance of adequately sampling ranges of rupture parameters when performing validations, as well as when simulating ground motions for future events.Graphical

Optimal intensity measures for probabilistic seismic demand models of steel moment frames

Selecting an optimal ground motion intensity measure (IM) is a vital step in the earthquake fragility analysis of building structures using probabilistic seismic demand models (PSDMs). This study proposes optimal IMs among 20 considered for seismic fragility analysis of structural steel moment frames in PSDMs. Five steel frames of different heights were selected to propose optimal IMs for steel frames between 2 and 20 stories. The IMs were evaluated using two engineering demand parameters (maximum interstory and roof drifts). Two characteristics of ground motions were investigated (pulse and non-pulse). The results revealed that velocity-related parameters (Housner intensity (HI) and peak ground velocity (PGV)) and spectral pseudo-acceleration at the first natural period (PSa(T1)) tend to be optimal IMs for steel moment frames. For maximum interstory drift, HI is suggested as the optimal IM for steel frames of 2–12 stories for both types of ground motions, while PGV is suggested for steel frames from 12 to 20 stories. Under maximum roof drift, PSa(T1) is the optimal IM for steel frames of all investigated stories subjected to either ground motion type. Peak ground acceleration, which is widely used as a ground motion IM, was observed to be unsuitable for all steel moment frames investigated in this study.

Ground Motion Simulations for the 19 January 2020 Jiashi, China, Earthquake Using Stochastic Finite‐Fault Approach

AbstractA 6.0‐magnitude (Mw) earthquake was reported to have occurred in Jiashi County, Xinjiang at 21:27 on 19 January 2020, Beijing time (13:27 UTC). This study applied a stochastic finite‐fault approach based on the dynamic corner frequency (EXSIM) to simulate 23 near‐field stations within a distance of 120 km from the epicenter. The stochastic finite‐fault approach is the simplest and most effective method for simulating high‐frequency ground motions. According to studies and empirical relationships, we estimated a region‐specific parameter (κ0) for use in simulations. In this study, two different slip models, namely, random and inverted slip models, were used to explain their influence on the simulation results. For most stations, the simulated seismic characteristics, such as the peak ground acceleration (PGA), pseudo spectral acceleration ,and Fourier acceleration spectrum, are highly compatible with the observed values in the frequency range (f > 1 Hz), indicating that the stochastic finite‐fault approach is not highly sensitive to input slip distributions and fault dimensions. The simulation results indicated no significance between the two slip models under high‐frequency conditions. Finally, based on the predicted PGA values of 1891 field points selected near the fault, the acceleration field of the Jiashi earthquake is plotted. The results show that the use of the acceleration time history predicted by modified EXSIM is feasible and practical in the high‐frequency band above 1 Hz.

A statistical study of inelastic displacement ratio spectrum for existing structures

AbstractDisplacement‐based design has gained importance due to the emergence of the performance‐based engineering, and it has now become desirable to estimate maximum (inelastic) displacements of structures for different levels of seismic hazard. Being closely related to damage, displacement (or drift) has become an important parameter necessary to meet various performance goals. It is considered convenient to estimate the inelastic displacement demand in a structure by multiplying the elastic displacement demand of the structure with a ratio called the inelastic displacement ratio. A comprehensive study is conducted for the parametric dependence of the inelastic displacement ratio in single‐degree‐of‐freedom (SDOF) systems with known relative lateral strengths, on strong motion duration, earthquake magnitude, epicentral distance, and geological site conditions. This study is different from the earlier studies of similar types in that other governing parameters are kept fixed while the effects of variations in any particular parameter are studied. This study is based on the generation of ensembles of synthetic accelerograms from a database of 1274 accelerograms recorded in western USA for the pseudospectral acceleration (PSA) spectra of given source and site parameters. It is found that strong motion duration may influence the inelastic displacement ratios, depending on the hysteretic properties of the oscillator, in the case of durations not much longer than 10 s. Earthquake magnitude has a significant influence on these ratios for the SDOF systems of most periods, while site geology appears to be important for the stiff oscillators. A scaling model is also proposed in this study for estimating the inelastic displacement ratio spectrum from a normalized relative velocity spectrum of the ground motion. The proposed model indirectly includes the effects of various governing parameters and is shown to preserve the trends available from the direct study.

An Improved Probabilistic Seismic Hazard Assessment of Tripura, India

The State of Tripura lies in northeast India which is considered to be one of the most seismically active regions of the world. In the present study, a realistic Probabilistic Seismic Hazard Assessment (PSHA) of Tripura State based on improved seismogenic sources considering layered polygonal sources corresponding to hypo-central depth range of 0 to 25 km, 25 to 70 km and 70 to 180 km, respectively and data driven selection of suitable Ground Motion Prediction Equations (GMPEs) in a logic tree framework is presented. Analyses have been carried out by formulating a layered seismogenic source zonation together with smooth-gridded seismicity. Using the limited accelerogram records available, most suitable GMPEs have been selected after performing a thorough quantitative assessment and thus the uncertainty in selecting appropriate GMPEs in PSHA has been addressed by combining them with proper weight factor. The computations of seismic hazard are carried out in a higher resolution of grid interval of 0.05 $\degree$ X 0.05 $\degree$. The probabilistic seismic hazard distribution in terms of Peak Ground Acceleration (PGA) and 5% damped Pseudo Spectral Acceleration (PSA) at different time periods for 10% and 2% probability of exceedance in 50 years at engineering bedrock level have been presented. The final results show significant improvements over the previous studies, which is reflecetd in the local variation of the hazard maps. The design response spectra at engineering bedrock level can be computed for any location in the study region from the hazard distributions. The results will be useful for earthquake resistant design and construction of structures in this region.

Regression analysis on ground motion parameters for the earthquakes (Mw≥4.0) in NE India with special emphasis on 3 Jan 2016 M6.7, Tamenglong earthquake

In the present study, ground motion parameters (GMPs) are estimated by processing 26 earthquake events containing 125 accelerogram records with 375 components that originated in NE, India, and its vicinity with special emphasis on the Jan 3, 2016, M6.7, Tamenglong Earthquake. Moreover, Ground Motion Prediction Equations were developed through multiple regression analysis on observed data of 8 GMPs namely, Peak Ground Acceleration, Peak Ground Velocity, Arias Intensity, Characteristics Intensity, Housner Intensity, Cumulative Absolute Velocity, Effective Design Acceleration, and Acceleration Spectrum Intensity. The developed equations are representative of statistics on changes in amplitudes of parameters with varying distances and magnitude in connection to Northeast India. Besides, newly developed GMPEs can be applied to 4–6.8 magnitude earthquakes and valid up to 525 km of distance. In the case of January 3, 2016, Mw = 6.7, Tamenglong earthquake, a total of 25 parameters are estimated from ground motion recordings. The highest Peak Ground Acceleration (PGA) of 0.05 (g) has been experienced by Kohima station along with Pseudo Spectral Acceleration of 0.2802 (g) at the frequency of 1.72 Hz. The peak pseudo-spectral accelerations for each recording site of the Tamenglong earthquake are perceived within the periods of 0.2s and 0.5s. These estimations help in the characterization of ground motion with varying distances and magnitude which is a prime input to rate damage potential of ground motion and seismic hazard analysis in Northeast India.

Regional Spectral Characteristics Derived Using the Generalized Inversion Technique and Applications to Stochastic Simulation of the 2021 Mw 6.1 Yangbi Earthquake

ABSTRACTIn this study, 334 accelerograms of 42 small-to-moderate earthquakes recorded at 36 strong-motion stations were used to investigate the ground-motion characteristics of the southwestern margin of the Sichuan–Yunnan rhombic block (SWM-SYRB), one of the most active seismic regions in China. The high-frequency attenuation parameter was estimated using the spectral decay method, and the site component (κ0) was fitted. The κ0 estimates decrease with the increasing time-averaged S-wave velocity of the uppermost 30 m (VS30). Using the generalized inversion technique, the source spectra, quality factor (Q), and site amplification were derived from the Fourier amplitude spectra (FAS). The obtained average stress drop for earthquakes occurred in SWM-SYRB was the second largest among various boundary areas of SYRB. The inverted Q model was Q(f)=115.1f0.616. The low Q structure that extends southwestward from the Songpan–Garze block to SWM-SYRB could be responsible for the strong regional attenuation of ground motion with distance. At frequencies above 10 Hz, the average site amplifications were influenced by the high-frequency attenuation effect. The site amplification of site class D reached a factor of 6 at 0.7 Hz. Moreover, it was observed that site amplification factors can be even higher when peak ground acceleration is larger than 0.8 m/s2. Finally, the obtained parameters were used in the stochastic finite-fault simulation method to reproduce the FAS, 5%-damped pseudospectral acceleration, and time series of the 2021 Mw 6.1 Yangbi earthquake. The simulated spectra properly matched the observations in a broad frequency band of 0.1–25 Hz. Furthermore, the simulated time series could generally represent the amplitude of the S-wave portion of observed ones.

Seismic Analysis of Double Unit Tunnel Form Building Subjected to Out-of-Plane Lateral Cyclic Loading

Most of the high-rise buildings for commercial and residential purposes in Malaysia are constructed using a tunnel formwork system. This type of building becomes a favor due to the fast construction and cost-effectiveness. However, the research on the behavior of Tunnel Form Building (TFB) under the seismic effect is still insufficient and requires further investigation. Therefore, the safety level of double unit TFB subjected to weak plane (out-of-plane) was investigated in this study. The TFB was designed using a non-seismic provision to represent an existing condominium building constructed in Selangor. Ten past earthquake records categorized as major, moderate, and low magnitudes were utilized. The behavior of the double unit TFB was analyzed using the Ruaumoko 2D program. The ultimate lateral load, displacement, pseudo-spectral acceleration (PSA), pseudo-spectral displacement (PSD), and mode shape of TFB were also analyzed. Based on the findings, most of the selected earthquake records exceeded the lateral capacity of TFB. The building experienced a major damage under 6.9 Richter scale of Imperial Valley, 7.3 Richter scale of San Joaquin Valley, and 7.9 Richter scale of Denali Earthquakes excitations. Therefore, these findings suggested if any similar magnitudes of unpredicted seismic events would occur in the future, significant damages may be experienced by the existing TFB in Malaysia. Doi: 10.28991/CEJ-2022-08-11-012 Full Text: PDF