Ground Motion Spectra Research Articles

Probabilistic generation of hazard‐consistent suites of fully non‐stationary seismic records

AbstractA novel, practical, and computationally efficient probabilistic methodology for the stochastic generation of suites of fully non‐stationary artificial accelerograms is presented. The proposed methodology ensures that the produced ground motion suites match a given target spectral mean and target variability for the whole period range of interest. This is achieved by first producing an ensemble of random target spectra with the given mean and variability and then using them to generate artificial, target spectrum‐compatible, acceleration time‐histories with spectral representation techniques. Spectral correlation can also be assumed for the generated ground motion spectra. Based on the same backbone, two different formulations are proposed for generating spectrum‐compatible acceleration time‐histories of the non‐stationary kind. The distinction between these two variants lies in the techniques employed for modeling the temporal and spectral modulation, focusing on the site‐compatibility of the produced records. The first approach uses past‐recorded seismic accelerograms as seed records, and the second proposes and uses a new, probabilistic time‐frequency modulating function. The outcome of the proposed methodology is suites containing site‐compatible ground motion time‐histories whose spectral mean and variability match those obtained from any of the usually employed target spectra used in the earthquake engineering practice. An online tool implementing the proposed methodology is also freely provided.

Empirical models for Fourier amplitude spectrum of ground-motion calibrated on data from the Iranian plateau

Ground-motion models (GMMs) are frequently used in engineering seismology to estimate ground motion intensities. The majority of GMMs predict the response spectral ordinates (such as spectral acceleration) of a single-degree-of-freedom oscillator because of their common application in engineering design practices. Response spectra show how an idealized structure reacts to applied ground motion; however, they do not necessarily represent the physics of ground motion. The functional forms of the response spectra GMMs are built around ideas taken from the Fourier spectral concept. Assuming the validity of Fourier spectral concepts in the response spectral domain could cause physically inexplainable effects. In this study, using a mixed-effects regression technique, we introduce four models capable of predicting the Fourier amplitude spectrum that investigates the impact of incorporating random-effect event and station terms and variations in using a mixed-effects regression technique in one or two steps using truncated dataset or all data (nontruncated dataset). All data consists of 2581 three-component strong ground motion data resulting from 424 events with magnitude ranging from 4.0 up to 7.4, from 1976 to 2020, and 706 stations. The truncated dataset’s records, events, and stations are reduced to 2071, 408, and 636, respectively. As part of this study, we develop GMMs to predict the Fourier amplitude spectrum for the Iranian plateau within the frequency range of 0.3–30 Hz. We adopted simple, functional forms for four models, and we included a limited number of predictors, namely Mw (moment magnitude), Rjb (Joyner–Boore distance), and VS30 (time-averaged shear-wave velocity in the top 30 m). Due to statistical analyses, the style-of-faulting term was excluded from the final functional forms. The robustness of the derived models is indicated by unbiased residual variation with predictor variables.

Prediction of Fourier Amplitude Spectrum of Ground Motion in Mexico City from Subduction Thrust Earthquakes

Mexico City, one of the largest cities in the world, experiences frequent, devastating interplate earthquakes that originate on the subduction thrust along the Pacific coast of Mexico more than 250 km away. A notorious example is the 19 September 1985 Michoacán earthquake (Mw 8.0) which killed ~ 10,000 persons and caused wide-spread destruction in the city. The main cause of seismic damage in Mexico City is its subsoil that amplifies the ground motion. In view of the seismic hazard faced by the city, a reliable estimation of ground motion during future earthquakes is of vital importance. We present a new ground motion prediction equation (GMPE) for the Fourier amplitude acceleration spectrum (FAS) from subduction thrust earthquakes along the Pacific coast of Mexico at the reference station, CU, located in the firm zone of Mexico City. The GMPE is derived via Bayesian regression analysis and is based on an enlarged set of recordings (1965-2020; 40 earthquakes; 250 ≤ R≤ 500 km; 5 ≤ Mw ≤ 8.0). An important feature of the new GMPE is that it includes a term to model different attenuation along different ray paths. The inclusion of this term leads to a reduction in the aleatory variability of the GMPE, particularly at high frequencies. Since spectral amplification of seismic waves with respect to CU is known at many sites in the city, the FAS at these sites can be computed if it is known at CU. The new GMPE has been incorporated in a fully Fourier-based probabilistic seismic hazard analysis of Mexico City.

Evaluation of the Inter-frequency Correlation of New Zealand CyberShake Crustal Earthquake Simulations

The inter-frequency correlation of ground-motion residuals is related to the width of peaks and troughs in the ground-motion spectra (either response spectra or Fourier amplitude spectra; FAS) and is therefore an essential component of ground-motion simulations for representing the variability of structural response. As such, this component of the simulations requires evaluation and validation when the intended application is seismic fragility and seismic risk. This article evaluates the CyberShake NZ [1] crustal earthquake ground-motion simulations for their inter-frequency correlation, including comparisons with an empirical model developed from a global catalogue of shallow crustal earthquakes in active tectonic regions, and with results from similar simulations (SCEC CyberShake; [2]). Compared with the empirical model, the CyberShake NZ simulations have a satisfactory level of total inter-frequency correlation between the frequencies 0.1 – 0.25 Hz. At frequencies above 0.25 Hz, the simulations have lower (statistically significant at 95% confidence level) total inter-frequency correlation than the empirical model and therefore require calibration. To calibrate the total correlation, it is useful to focus on the correlation of the residual components. The between-event residual correlations, physically related to source effects (e.g., stress drop) which drive ground motions over a broad frequency range, are low at frequencies greater than about 0.25 Hz. Modifications to the cross-correlation between source parameters in the kinematic rupture generator can improve the inter-frequency correlations in this range [3]. The between-site residual correlations, which represents the correlation between frequencies of the systematic site amplification deviations, are larger (statistically significant at 95% confidence level) than the empirical model for frequencies less than about 0.5 Hz. We postulate that this relates to the relative simplicity of site amplification methods in the simulations, which feature less variability than the amplification observed in the data. Additional insight would be gained from future evaluations accounting for repeatable path and basin effects, using simulations with refined or alternative seismic velocity models, and using simulations with a higher crossover frequency to deterministic methods (e.g., 1 Hz or higher).

Equivalent Near-Field Corner Frequency Analysis of 3D Dynamic Rupture Simulations Reveals Dynamic Source Effects

Abstract Dynamic rupture simulations generate synthetic waveforms that account for nonlinear source and path complexity. Here, we analyze millions of spatially dense waveforms from 3D dynamic rupture simulations in a novel way to illuminate the spectral fingerprints of earthquake physics. We define a Brune-type equivalent near-field corner frequency (fc) to analyze the spatial variability of ground-motion spectra and unravel their link to source complexity. We first investigate a simple 3D strike-slip setup, including an asperity and a barrier, and illustrate basic relations between source properties and fc variations. Next, we analyze >13,000,000 synthetic near-field strong-motion waveforms generated in three high-resolution dynamic rupture simulations of real earthquakes, the 2019 Mw 7.1 Ridgecrest mainshock, the Mw 6.4 Searles Valley foreshock, and the 1992 Mw 7.3 Landers earthquake. All scenarios consider 3D fault geometries, topography, off-fault plasticity, viscoelastic attenuation, and 3D velocity structure and resolve frequencies up to 1–2 Hz. Our analysis reveals pronounced and localized patterns of elevated fc, specifically in the vertical components. We validate such fc variability with observed near-fault spectra. Using isochrone analysis, we identify the complex dynamic mechanisms that explain rays of elevated fc and cause unexpectedly impulsive, localized, vertical ground motions. Although the high vertical frequencies are also associated with path effects, rupture directivity, and coalescence of multiple rupture fronts, we show that they are dominantly caused by rake-rotated surface-breaking rupture fronts that decelerate due to fault heterogeneities or geometric complexity. Our findings highlight the potential of spatially dense ground-motion observations to further our understanding of earthquake physics directly from near-field data. Observed near-field fc variability may inform on directivity, surface rupture, and slip segmentation. Physics-based models can identify “what to look for,” for example, in the potentially vast amount of near-field large array or distributed acoustic sensing data.

Variability of response spectra of single-path ground-motion record pairs

To improve the accuracy of seismic hazard analysis, understanding the uncertainty of the prediction of the ground-motion amplitude for a specific site owing to a specific source is important. In this study, the variability of the acceleration response spectra of single-path ground motion was evaluated using record pairs obtained from two earthquakes at the same site with the same magnitude, location, and focal mechanism, recorded by high-density strong-motion observation networks in Japan. The natural log standard deviations of the single-path ground motions varied with the period and were distributed in the range of approximately 0.3–0.5. Even if an empirical ground-motion prediction model that accurately models the characteristics of single-path ground motions could be developed, avoiding this variability in the prediction is difficult. The standard deviation of the within-event residuals was smaller at larger distances, and the period of the maximum standard deviation tended to increase as the earthquake magnitude increased. These features may be attributed to differences in the source characteristics of each earthquake. These findings will be useful for the development of advanced empirical ground-motion models and for improving the accuracy of seismic hazard analysis.

An adapted LSTM-DRRNet approach for predicting floor acceleration response spectrum

The floor response spectrum is an essential element in designing non-structural components (NSC) under earthquakes. However, most available approaches for floor response spectrum estimation involve complex modeling work, require intensive computational resources, and lack generalizability. To address these limitations, this paper proposes a novel deep-learning-based methodology to provide a generalized estimate of nonlinear floor response spectra, which is composed of a bidirectional convolutional long short-term memory network with an attention mechanism (ACN-BiLSTM) and a deep residual regression network (DRRNet). ACN-BiLSTM uses one-dimensional convolution to extract high-dimensional abstract features of ground motion spectrum in each period. The attention mechanism and multi-scale sliding time window are used to improve the network’s convergence speed and prediction accuracy. DRRNet uses deep one-dimensional convolution to build a residual shortcut connection, which delivers the proportional relationship between floor response spectrum at different heights. With the input of the ground motion acceleration spectrum and structural characteristics, the proposed method can estimate the nonlinear floor acceleration response spectrum on any floor of a building. To demonstrate its efficacy, the proposed approach is applied to a dataset that includes floor response spectra of 56 buildings subjected to 195 ground motions. The application results indicate that the proposed approach can effectively and reliably predict the nonlinear acceleration response spectrum with an accuracy of 97.29%. Such an efficient method is promising in advancing the seismic design of non-structural components.

Dimensionality study of ground motion spectra through nonlinear principal component analysis

Dimensionality study of ground motion spectra through nonlinear principal component analysis

Influence of seawater depth on offshore ground motion characteristics and seismic responses of sea-crossing cable-stayed bridges

This paper studies the effect of seawater depth on offshore earthquake motion characteristics and seismic response of bridges. By analyzing the offshore seismic data recorded by the K-NET during 2006–2021, the horizontal amplification coefficient spectrum and V/H spectral ratio of offshore ground motions were compared for various offshore stations at different seawater depths. Moreover, a numerical model simulating the propagation process of seismic waves in the seabed was developed to investigate the effects of seawater depth and site conditions on offshore ground motions. Finally, a site-seawater-pile foundation-cable-stayed bridge coupling model was created to study the influence of seawater depth on the seismic responses of sea-crossing cable-stayed bridges. The results reveal that the vertical response spectrum of offshore ground motion in deeper seawater is lower for periods longer than 0.3 s. The numerical models reveal that seawater has a suppression effect on the P wave near the resonance frequency of the seawater layer. Due to the hydrodynamic effect, the longitudinal bridge seismic response is significantly amplified. The amplification effect becomes more obvious with an increase in seawater depth. Therefore, it is important to consider the influence of the seawater layer in the seismic design of sea-crossing bridges.

Effects of response spectrum of pulse-like ground motion on stochastic seismic response of tunnel

It is widely accepted that near-fault pulse-like ground motions potentially cause more severe damage to structures than ordinary ground motions. However, the effects of stochastic pulse-like ground motions on underground structures are not effectively considered. The impacts of response spectra of pulse-like ground motions on seismic response are also unclear. Hence, this study utilizes an underground tunnel to investigate the effects of response spectra of pulse-like ground motions on the stochastic seismic response by combining a pulse-like ground motion simulation method and a finite element method. The combination procedure enables stochastic seismic response analysis under spectrum-compatible pulse-like/ordinary ground motions. The finite element model considers the nonlinear dynamic properties of soil and soil–structure interaction. Monte Carlo simulations are carried out to quantify uncertainties of stochastic tunnel response. Results show that pulse-like ground motions cause larger bending moments for tunnel lining even when they match the same target spectrum of ordinary ground motions. Furthermore, the bending moment of tunnel lining is significantly amplified when the spectral acceleration of pulse-like ground motion contains bulges or multiple peaks in the ranges of 1 s–6 s. Therefore, the seismic risk of tunnels may be significantly underestimated in the near-fault regions without considering pulse-like ground motions and their spectral acceleration characteristics.

A Method to Simulate High-Frequency Decay of Acceleration Spectra of Ground Motions without the Need for Kappa or fmax Filters

ABSTRACTA well-known difficulty in the popular simulations of earthquake ground motions for seismic hazard assessment using the point-source model is overprediction of high-frequency spectra. Ad hoc high-cut filtering, known as fmax or the kappa effect, is required to render the high-frequency content to match observations. The physical origin of such filtering’s realistically occurring in nature has remained largely unclear. The difficulty is naturally resolved if (1) the shape of the source time function is allowed to deviate from the traditional form radiating the omega-square spectrum and replaced by the function producing the high-frequency falloff not equal to the power of 2, and (2) the high-frequency suppression due to finite-fault dimensions (the finite-fault directivity) is accounted for. The verification database consists of 20 earthquakes in the magnitude range from 4 to 6 recorded in boreholes on rock sites in southwestern Japan by the KiK-net network. The events are those observed by the greatest number of stations. Path-effect corrections using three independently determined attenuation laws lead to the isolation of the average observed source spectra. Simulations of the spectra through the kappa-filtered omega-square model offer no advantage over those using the omega-n source model combined with the finite-fault effect. The inclusion of fault directivity thus eliminates the need for kappa filtering. The high-frequency suppression, required to simulate realistic ground-motion spectra, can be fully explained by the source effect with clear physical meaning.

New generalized ANN-based hybrid broadband response spectra generator using physics-based simulations

Estimation of the seismic risk associated with infrastructures requires site-specific seismic hazard studies. Further, for nonlinear time history analysis, one requires broadband ground motion. In modern times, physics-based simulations (PBS) for deriving the ground motion for future earthquakes have been considered. The PBS helps decrease the uncertainties related to hazard estimation compared to ground motion prediction equations. The PBS methods have a specific frequency threshold limit resulting from high computational demand. Hence, hybrid methods are required to attain broadband spectra for the simulated ground motion. This study uses a new artificial neural network (ANN)-based model to generate broadband ground motion spectra using the low-frequency spectral acceleration from PBS, source, path, and site parameters as input variables. A detailed parametric study and performance evaluation was made to identify the optimal input parameters in conjunction with the best-suited ANN architecture. The performance of the ANN model is demonstrated for Iwate (\(M_w\) 6.9, 2008) earthquake. We found that the predicted values from the developed ANN model agree with the recorded data. Furthermore, time histories are generated using the spectral ordinate matching technique from the estimated broadband spectra.

Parametric spectral inversion of seismic source, path and site parameters: application to northeast Italy

SUMMARY Strong ground motion prediction is a fundamental topic in the field of engineering seismology, as it provides the input for seismic hazard studies as well as for vulnerability and risk assessment. The spectral modelling approach can provide a realistic representation of ground motion behaviour, possibly including its frequency variability, as the full ground motion spectrum is modelled analytically. In its parametric form, this approach requires a careful calibration of the model, starting from empirical observations and fitting the source, path and the site-specific response assuming a predefined physically constrained functional form. This study explores the use of spectral modelling for a study area in northeast Italy, at the border with Slovenia and Austria. It is based on the parametrization of seismic source and attenuation effects, and it also allows to estimate site effects, as a by-product. The main innovation with respect to standard spectral modelling is the inclusion of dedicated uncertainty estimators in the functional form. Parametric inversion of source and path attenuation is performed on a data set corresponding to 23 events recorded by 24 stations located within the target area. The modular inversion setup allows to properly include a priori constraints in the mathematical solution to reduce trade-off between variables. Spectral amplification at each site is defined with respect to the network average rock condition, and its frequency-dependent component is estimated from residual analysis after the inversion. Inverted source parameters are comparable with reference values for the region available from literature (with seismic moments between ${10}^{13}$ and ${10}^{15}$ N·m, and related stress drop values in the range $1.5 - 15.5\ {\rm{MPa}}$); the same is also true for average attenuation properties (e.g. apparent frequency-independent attenuation quality factor ${Q}_0$ of $1145$). For a selection of stations with available characterization based on different methods, a preliminary comparison of site-specific response functions shows that both the frequency value and amplitude of the main amplification peaks are well recovered. These encouraging results open to the possibility of subsequently using the calibrated model for forward modelling purposes.

Stochastic ground motion models to NGA‐West2 and NGA‐Sub databases using Bayesian neural network

AbstractGround motion models (GMMs) are traditionally developed from a frequentist approach. The Bayesian framework has received recent attention in developing nonergodic models, measuring uncertainty, or updating the model with additional data. However, no neural networks are developed to date in this framework to predict ground motion parameters or spectra. Hence, the present work develops a probabilistic Bayesian neural network (PBNN) to next‐generation attenuation – West2 and Subduction databases using variational inference with mean‐field assumption. Network inputs are magnitude, rupture distance, hypocentral depth, shear wave velocity, style of faulting, and region flags; outputs are peak ground values and response spectra. Both models have two hidden layers with seven neurons in each hidden layer. The models are verified for potential overfit, and their performance is validated through the parametric study by varying inputs. The output of a deterministic model is a point estimate. Considering probabilistic layers in hidden and output layers enables the model to capture within‐model epistemic uncertainty and aleatory variability. Obtained aleatory standard deviations are consistent with other models. Mean epistemic uncertainty and aleatory variability are in the range 0.07–0.10 and 0.62–0.78 (ln units) for NGA‐West2 and 0.09–0.16 and 0.67–0.95 for NGA‐Sub models, respectively. The correlation coefficients between recorded and overall mean predictions ranged from 0.94 to 0.97 for NGA‐the West2 model and from 0.91 to 0.95 for the NGA‐Sub models. Network performance for out‐of‐training inputs showed increased epistemic deviations with no effect on aleatory deviations.

Interstory drift based scaling of bi‐directional ground motions

AbstractThe interstory drift‐based scaling procedure (IDS) developed recently by the authors for plane frames under single component horizontal ground motions, has been extended to three‐dimensional structures possessing torsional coupling under bi‐axial ground motions which are represented by their geometric mean spectrum. The ground motion‐scaling factor is defined as the ratio of average interstory drift along building height under target spectrum versus that under the associated ground motion spectrum. Hence, scaling is conditioned on structural response, which is in turn a function of seismic intensity. IDS for 3D systems is applied to 20‐story and 3‐story concrete space frames with mass and stiffness eccentricity, respectively. Accuracy and efficiency of the IDS procedure is assessed under a set of near‐fault strong motion pairs from large magnitude events. The results revealed that the proposed procedure is accurate and noticeably more efficient as compared to conventional procedures suggested in seismic codes and in literature. Further, the intensity measure employed in the IDS procedure is proved as a good predictor of fundamental demand measures (maximum interstory drift ratio and maximum plastic rotations) obtained from nonlinear dynamic analyses under individual ground motion pairs. Hence, employing the intensity measure of IDS for ground motion scaling in intensity‐based evaluation of structures is proposed for reliable estimation of structural performance under code‐prescribed seismic hazard.

On the Limitations of Spectral Source Parameter Estimation for Minor and Microearthquakes

ABSTRACTReliable estimation of earthquake source parameters is fundamental to improve our understanding of earthquake source physics and for ground-motion modeling in seismic hazard assessment. Nowadays, methods traditionally used for investigating the source parameters of earthquakes with Mw≥3, such as spectral fitting or spectral ratio approaches, are also extensively applied to smaller magnitude events because of the increase in the number of stations and the more common borehole installations. However, when working with recordings of such minor and microearthquakes, significant limitations of the usable frequency range spanned by the spectra arise. At the lower end, signal-to-noise ratio constraints limit the usage of low frequencies, whereas at the upper end, the sampling rates of typical seismological networks as well as high-frequency attenuation can be limiting factors. In addition, earthquake source parameters determined from ground-motion spectra are known to exhibit potentially serious trade-offs, in particular the corner frequency and high-frequency attenuation. In this study, we go beyond the typical discussion of these trade-offs using simplistic spectral models by investigating the impact of the background wave propagation model on the source parameter trade-offs as well as its effect on the feasibility of obtaining useful source parameters by means of spectral fitting for minor and microevents. The analysis takes advantage of ad hoc simulated synthetic seismograms with well-defined underlying background propagation models and considers increasing complications in these models (intrinsic and scattering attenuation). The results show that with given realistic background models and usable frequency bands, the source parameter estimation for minor and microevents can be significantly biased, and not surprisingly, this bias is mainly affecting the estimation of the corner frequency. We highlight the inherent limitations of joint spectral fitting approaches for the determination of source parameters from minor and microearthquakes, which should always be viewed with great caution when physically interpreted.

Determining the Optimal Scalar Intensity Measure of Floor Communication Towers

Various structural types and ground motion characteristics lead to distinct intensity measures of structural seismic performance. For the lattice high-rise steel structure of communication towers, determining the intensity measures to adjust ground motion is critical. Additionally, a crucial problem is whether the ground motion intensity parameters of pulse-like ground motion and ordinary ground motion are consistent. In this study, a standard floor four-leg angle steeled communication tower was considered the study object, and 50 pulse-like ground motions and 50 ordinary ground motions were identified to form a pulse-like ground motion set and ordinary ground motion set, respectively. For comparative analyses, 15 ground motion parameters, including amplitude, spectrum, duration, and energy parameters, were selected. The results revealed that for the lattice towers, such as communication tower, under the action of pulse-like ground motion or ordinary ground motion, efficiency, practicability, and sufficiency should be considered. Furthermore, the most suitable intensity measure was the spectral acceleration corresponding to the natural period of the tower. This study provides a basis for selecting the ground motion for dynamic time history analysis of the lattice steel tower.

Collapse assessment of low-rise reinforced concrete special moment resisting frame systems using a simplified method

In this study, a simplified method is proposed to generate collapse fragility curves for low-rise reinforced concrete special moment resisting frame (SMRF) systems. Capacity curves are developed without carrying out structural modeling and nonlinear static analysis, to obtain equivalent SDOF parameters. Ground motion spectra that matches the conditional spectrum (CS) at specified seismic intensity levels are statistically generated and a displacement-based assessment procedure instead of nonlinear response history analysis (NLRHA) is adopted, to obtain the peak displacements necessary for the generation of collapse fragility curves, with and without considering uncertainty in modeling parameters. The proposed simplified method is applied to 3- and 5-story low-rise reinforced concrete SMRF systems for the generation of collapse fragility curves. In addition, a 8-story reinforced concrete SMRF system is considered to examine the applicability of the proposed simplified method to non low-rise reinforced concrete SMRF systems. The results show that the collapse fragility curves generated by using the proposed simplified method are in good agreement with the curves developed using NLRHA for the 3- and 5-story low-rise reinforced concrete SMRF systems; however, such agreement is not observed for the 8-story non low-rise reinforced concrete SMRF system.

Shallow soil effects for contrasting PGAs at nearby strong-motion stations during the 2017, Mj 5.2, southern Akita Prefecture earthquake

On September 8, 2017, an earthquake of Mj 5.2 occurred with the epicenter in southern Akita Prefecture, Japan, at 22:23 local time. According to the Japan Meteorological Agency (JMA), the focal depth was 9 km. Many strong-motion stations of K-NET and KiK-net recorded ground motions from the earthquake. The maximum horizontal vector peak ground acceleration (PGA) of approximately 136 cm/s2 was recorded at one of the KiK-net stations at an epicentral distance of about 8 km. However, despite being 37 km and 53 km far from the epicenter, two stations recorded PGAs of approximately 126 and 113 cm/s2, respectively, similar to that near the epicenter. Even though these PGAs are not rare, we found that the PGAs at the two sites strongly deviated from the median values suggested by a ground motion prediction equation (GMPE), while the nearby sites generally followed the GMPE. Available velocity models showed that shallow shear wave velocities, especially in the top 5 m, were lower (i.e., the soils were softer) at the two sites compared to those at their nearest neighboring sites. We compared the ratios of the PGAs and peak ground velocities (PGVs) at the two sites with respect to their neighboring sites for many earthquakes covering a wide range of magnitudes and azimuths. We found that the PGAs and PGVs at the two sites were systematically larger than those at the adjacent sites. Linear theoretical site amplifications using the available soil models gave peak frequencies around 6-8 Hz at the larger PGA sites. Bandpass-filtered records showed significantly larger PGAs around these frequencies at the larger PGA sites. The above results showed that local site condition is one of the major contributing factors to induce large PGAs. Furthermore, softer sites experience more substantial nonlinear site amplification than the stiffer sites when input motions exceed some threshold PGAs. This latter effect means that the softer sites can produce a variety of ground motion spectra. Nevertheless, the degree of damage to built structures depends on several factors, including the design and quality of construction. We expect that this study contributes to developing improved microzonation maps for earthquake disaster mitigation.

Performance of structures in İzmir after the Samos island earthquake.

The October 30, 2020 Earthquake caused unexpectedly significant damage in İzmir considering its distance to the city. This paper evaluates the recorded ground motions, summarizes the performance of structures affected from the earthquake with emphasis on the reasons of damage. A detailed damage assessment was carried out by the Earthquake Engineering Research Center of Middle East Technical University to compile data on the damage of RC and masonry buildings. It was observed that majority of the damage was concentrated in the Bayraklı district due to its peculiar soil properties where many 7–10 story mid-rise RC buildings suffered heavy damage and collapse. The level of amplified ground motions combined with deficiencies of apparently non-code compliant buildings exacerbated the damage. The main reasons of damage were mainly attributed to the presence of soft stories, lack of proper detailing, poor construction quality, presence of heavy overhangs, and hence significant lack of code-compliance in essence. The influence of infill walls on seismic performance of deficient and inadequate buildings was clearly seen in this earthquake. This paper also discusses seismic code requirements in effect and their influence on the observed building performance. The recorded ground motions were compared with the code spectra to evaluate the performance of the buildings. The code response spectra were found to be well above the recorded ground motion spectra at the sites where significant damage was observed.