Joyner-Boore Distance Research Articles

A Classification Method of Earthquake Ground Motion Records Based on the Results of K-Means Clustering Analysis

This paper presents a classification method for earthquake ground motion records utilizing the results of K-means cluster analysis. The moment magnitude and Joyner–Boore distance are utilized as the primary parameters for clustering the earthquake ground motion records. The classification boundaries are established through an examination of moment magnitude ranges, Joyner–Boore distance ranges, and spectral characteristics within each cluster. In this study, a comprehensive dataset comprising 7627 horizontal earthquake acceleration records was meticulously curated for analysis. The data were subjected to separate clustering and grouping procedures, allowing for insightful comparisons between the resultant clusters. Significant disparities in spectral characteristics across the classification groups were demonstrated. These differences become particularly pronounced when a moment magnitude threshold of 6 and a Joyner–Boore distance threshold of 140 km are employed to categorize the ground motion records. The approach underscores the substantial impact of classification based on earthquake ground motion spectral characteristics, while also mitigating the potential instabilities inherent in cluster analysis results. A refined and quantitatively robust framework for understanding and categorizing earthquake ground motions is provided, offering valuable insights for seismic data analysis and contributing to more accurate and reliable assessments of seismic activity.

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.

Hybrid Empirical Ground-Motion Models for the Island of Hawaii Based on an Updated Strong Ground-Motion Database

ABSTRACT In this study, we develop ground-motion models (GMMs) for the Island of Hawaii. This area has been the site of several significant earthquake events with a growing database of strong ground-motion observations. Ground-motion modeling on the Island of Hawaii is challenging due to different anelastic attenuation characteristics, the volcanic origin of some of the events, and event depth distribution. Only a few GMMs have been developed for the Island of Hawaii. In this study, we apply a hybrid empirical method (HEM) to develop two separate GMMs for shallow (hypocentral depth ≤ 20 km) and deep (hypocentral depth > 20 km) earthquakes on the Island of Hawaii. We utilize the ratio of the stochastic point-source model in the target and host regions as an appropriate adjustment factor. We apply these adjustment factors to convert the GMMs from the host (western North America) to the target (Island of Hawaii) region. We considered five GMMs proposed in the Next Generation Attenuation Phase 2 project by the Pacific Earthquake Engineering Research Center to model ground motions in the host region. We developed GMMs to predict peak ground acceleration and 5%-damped pseudospectral acceleration at periods T = 0.01–10 s, for moment magnitudes (M) in the range of 3–7.5, and for Joyner–Boore distances in the RJB≤200 km range. The applicability of HEM to develop GMMs for the Island of Hawaii and the growing strong ground-motion data result in further improvements in the capability of GMMs.

Directionality and polarization of response spectral ordinates in the 2023 Kahramanmaras, Türkiye earthquake doublet

Until recently, the orientation of maximum horizontal spectral response was generally believed to not have a predominant orientation at rupture distances greater than 5 km. However, a recent study found that the orientation of maximum spectral response for strike-slip earthquakes in the NGA-West2 database tends to occur close to the epicentral transverse orientation, that is, an orientation perpendicular to a line connecting the epicenter to the station. This article investigates directionality in the 6 February 2023 Türkiye doublet earthquakes ( Mw 7.8 and 7.5) with strike-slip faulting. The orientation of the maximum response of 5%-damped linear elastic oscillators was studied. The spatial distribution of the level of polarization, which in this article refers to the amount of directionality, and intensities at specific orientations were also studied. The maximum spectral response was found to occur systematically close to the epicentral transverse orientation, consistent with previous observations for other strike-slip earthquakes. For the Mw 7.8 event where the location of maximum slip was relatively far from the epicenter, it was found that the orientation of maximum spectral response is, on average, closer to the maximum slip transverse orientation (i.e. perpendicular to a line connecting the station to the surface projection of the point of maximum slip) when compared to the epicentral transverse orientation over most period ranges. This suggests that the maximum slip transverse orientation may be a better estimator for determining the orientation of maximum spectral response in large-magnitude strike-slip earthquakes, although further study using more events is warranted. Polarized motions were observed over large geographical areas, and the orientation of maximum spectral response was found to be close to the epicentral or maximum slip transverse for Joyner–Boore distances up to the farthest studied (400 km). These findings further support the case for the development of orientation-dependent ground motion models for strike-slip earthquakes.

An Empirical Spectral Ground-Motion Model for Iran Using Truncated Iranian Strong-Motion Database Enriched by Near-Field Records

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

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

Empirical Distance Metrics Relationships and Uncertainties in Seismic Hazard Assessment

ABSTRACTThe seismic hazard of an area is determined based on the ground motion observed at that site. The intensity of the ground motion can be predicted using ground -motion models (GMMs). GMMs typically use distance metrics such as the Joyner–Boore distance (RJB) and the rupture distance (RRUP). However, apart from RJB and RRUP, probabilistic seismic hazard analysis (PSHA) also utilizes point-source-based distances like the epicentral distance (REPI) and the hypocentral distance (RHYP). These distance metrics are used for point sources when the fault geometry is unknown or is ignored. To obtain an accurate seismic hazard of an area, we need to determine the relationship between the distance metrics. In this study, we develop empirical relationships between RJB and various other distance metrics. This method avoids conducting computationally intensive tasks such as computing finite-fault-based distances for different fault geometry of a virtual rupture plane for each point source. The empirical equations provide the relation between RJB and target distance metric (Rtarget) based on the magnitude of the earthquake and the dip angle of the fault. In addition, we also require the depth to the top of the rupture to calculate RHYP. We discuss the steps to include the variability due to the conversion of the distance metrics in the PSHA. We have compared the results of this study with other published studies for distance conversion. A simple PSHA study of a circular area of 100 km using Pezeshk et al. (2011) as the GMM determined an increase in hazard using the proposed empirical equations and their uncertainties. The equations developed in this study can be directly applied in PSHA and are independent of the GMMs used for seismic hazard calculations. The equations can also be used for different fault geometries with a range of dip angles varying from 10° to 90°, for magnitudes 5.0–8.0, and distances up to 200 km. We have focused on the central and eastern United States.

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.

Ground Motion Models for Non-Spectral Intensity Measures Based on the Iranian Database

ABSTRACT An Iranian earthquake database has been employed to propose local empirical equations to predict non-spectral ground motion intensity measures, including Arias intensity, cumulative absolute velocity and duration of ground motions. The significant duration models have been considered 5% – 75% and 5% – 95% of Arias intensity in analyses. The bracketed and uniform duration models were proposed for absolute or relative acceleration thresholds, including 0.025g, 0.05g, 0.1g 0.025PGA, 0.05PGA and 0.1PGA. In this study, we used an updated dataset consisting of 2965 three-component time histories from 654 seismic events with the magnitude range 3.5 to 7.7 at distances less than 300 km recorded between 1975 and 2019. The functional form of the proposed models consists of some variables, including moment magnitude (Mw), Joyner-Boore distance (RJB), average velocity of shear waves for the upper 30-m depth (Vs30), and faulting mechanisms. The random-effects algorithm is used for conducting the regression analysis, which considers inter-event and intra-event error terms, separately. To verify the trend of attenuation in the proposed models, some comparisons have been made between the proposed models in the current study and those developed for other similar regions.

Characteristics of Strong Ground Motions in the 30 October 2020, MW6.9 Aegean Sea Earthquake

The eastern parts of the Aegean Sea were struck by a destructive MW 6.9 earthquake on 30 October 2020 at 11:51:27 UTC. The earthquake ruptured an East-West trending normal fault in the Aegean Sea between the northern coast of Samos Island and the southern coast of İzmir and also triggered a medium level tsunami and thousands of aftershocks across the region. 119 fatalities, 1,051 injuries, and many collapsed buildings were reported due to the earthquake in the affected region. The most catastrophic consequences of the earthquake were registered in the Bayraklı and Bornova districts, which are built on a deep alluvial Basin approximately 60–70 km away from the epicentre of the mainshock. This paper explains the damage with an extensive dataset of ground motion records of the mainshock and aftershocks, which are provided by both Greek and Turkish networks. A set of ground motion parameters such as peak ordinates, spectral quantities, intensity measures and duration parameters are calculated and analysed. The closest softer soil station in Samos Island produces the highest peak ground acceleration and velocity. The ground motion models employed commonly for the region overestimate the observed data beyond 60–70 km of Joyner-Boore distance except for the recently published local ground motion model, which utilises local earthquakes in the derivation of the model. Contrary to expectations, stiff soil recordings exhibit considerable spectral accelerations in the long period region, similar to those in soft soils. The calculated ground motion parameters are correlated with the results of the hybrid reconnaissance mission, organized by the Earthquake Engineering Field Investigation Team (EEFIT). Although the peak values and regarded intensity measures clearly highlight the variability in soil conditions in the most damaged area (Bayraklı and Bornova), velocity-based ground motion parameters seem to be the more responsive damage indicators. The spectral shapes of the normalised response spectra in the İzmir Basin are not compatible with the 2018 Turkish seismic code spectrum whereas their response spectra are below the 475-years return period design spectra provided in outdated and current Turkish seismic codes.

IMPA versus Cloud Analysis and IDA: Different Methods to Evaluate Structural Seismic Fragility

Well-known methods for seismic performance assessment, such as incremental dynamic analysis (IDA), multi-stripes analysis (MSA) and the cloud method, involve nonlinear response time-history analyses to characterize the relationship between the chosen damage measure versus intensity measure. Over the past two decades, many authors have proposed simplified procedures or nonlinear static approaches to develop fragility. In these procedures, the capacity of the system is evaluated by nonlinear static procedures (i.e., the capacity spectrum method (CSM), the N2 method, modal pushover analysis (MPA)) and the demand is derived by response spectra. In addition to the familiar ones, incremental modal pushover analysis (IMPA) is a novel nonlinear static procedure proposed in recent years, and it is used in this research to present an IM-based fragility estimation. The accuracy and effectiveness of different methods to assess vulnerability are investigated by comparing fragility curves derived by MPA-based cloud analysis, IMPA and cloud analysis against IDA. The comparison gives valuable insights on the influence of scaling on different sets of records; however, a more extended validation is needed to confirm the obtained results and draw more general conclusions. Results arise from two relatively small bins of record motions differing by ranges of Joyner-Boore distance and scattered in a range of magnitude are presented.

Near-Source Ground Motions and Their Variability Derived from Dynamic Rupture Simulations Constrained by NGA-West2 GMPEs

ABSTRACTEmpirical ground-motion prediction equations (GMPEs) lack a sufficient number of measurements at near-source distances. Seismologists strive to supplement the missing data by physics-based strong ground-motion modeling. Here, we build a database of ~3000 dynamic rupture scenarios, assuming a vertical strike-slip fault of 36 × 20 km embedded in a 1D layered elastic medium and linear slip-weakening friction with heterogeneous parameters along the fault. The database is built by a Monte Carlo procedure to follow median and variability of Next Generation Attenuation-West2 Project GMPEs by Boore et al. (2014) at Joyner–Boore distances 10–80 km. The synthetic events span a magnitude range of 5.8–6.8 and have static stress drops between 5 and 40 MPa. These events are used to simulate ground motions at near-source stations within 5 km from the fault. The synthetic ground motions saturate at the near-source distances, and their variability increases at the near stations compared to the distant ones. In the synthetic database, the within-event and between-event variability are extracted for the near and distant stations employing a mixed-effect model. The within-event variability is lower than its empirical value, only weakly dependent on period, and generally larger for the near stations than for the distant ones. The between-event variability is by 1/4 lower than its empirical value at periods >1 s. We show that this can be reconciled by considering epistemic error in Mw when determining GMPEs, which is not present in the synthetic data.

A hybrid genetic algorithm-neural network model for power spectral density compatible ground motion prediction

In this paper, the utility of power spectral density (PSD) in ground motion prediction for hazard analysis is examined. The main advantage of PSD is that the area under PSD of excitation gives the energy of the excitation and it is structure independent. The PSD of ground motion from past earthquakes and properties of PSD in terms of spectral moments are studied. 1487 accelerograms from 25 major past earthquakes with magnitude ranging from 4.9 to 7.9 taken from the ‘Pacific Earthquake Engineering Research Centre – Next Generation Attenuation’ database are considered. PSD of past ground motion data is used to form a hybrid genetic algorithm-neural network based attenuation relationship with magnitude of earthquake, Joyner-Boore distance and shear-wave velocity. PSD compatible time histories are generated using the proposed model. An application of the proposed model is demonstrated by developing a uniform hazard power spectral density for Delhi with a return period of 2500 years.

A ground motion prediction equation for filtered incremental velocity, FIV3

Filtered incremental velocity, FIV3, is a recently proposed and very promising intensity measure for seismic collapse risk assessment. However, no ground motion prediction equation currently exists that enables its complete implementation in probabilistic seismic hazard analysis or in seismic performance assessment of structures. This paper presents a model for the estimation of the random horizontal component of FIV3 for stiff soil sites, moment magnitudes between 5 and 8, and Joyner-Boore distances between 0 and 150 km. Results from this study show that the uncertainty in the estimation of FIV3 is considerably lower than the one provided by current models for pseudo-acceleration spectral ordinates. This low dispersion of FIV3 results in a reduction in the uncertainty in the ordinates of seismic hazard curves, which ultimately improves the reliability of the estimation of the collapse risk of structures.

Scaling of Vertical Component of Seismic Ground Motion

Three-dimensional time history analysis has become a demand for the majority of updated building codes. A vast literature has addressed the selecting and scaling of horizontal component of earthquake ground motion. Meanwhile, the scaling of vertical component has been less of a concern. This paper investigates the suggestion of using the same scaling factor of horizontal component of ground motion to scale its vertical counterpart. A data set consists of 6409 mainshock records with vertical and orientation independent geometric rotated (GMRotD50) response spectra with 5% damping is used. Even though ASCE7-16 among other international codes recommends to use the same scaling factor for horizontal component and its vertical counterpart, this paper shows that scaling factor of vertical component trends an extreme variation from its horizontal counterpart for various soil classes, different magnitudes and over a wide range of Joyner-Boore distances. Results illustrate that the ratio of vertical to horizontal scaling factors has a strong negative relationship with the ratio of vertical to horizontal peak ground acceleration. Earthquake magnitude has no significant role on the ratio of vertical to horizontal scaling factors. A gradual increase is observed in the studied ratio over a wide range of Joyner-Boore distances. The paper ends up with simplified equations to calculate the scaling factor of vertical component in regards with the scaling factor of its GMRotD50 horizontal counterpart based on the (V/H)PGA ratio of the recorded components. Robust statistics manifest the goodness of the developed equations.

Assessing Predictive Capability of Ground‐Motion Models for Probabilistic Seismic Hazard in Iran

Abstract We assessed the applicability of several ground‐motion models (GMMs) against Iran’s local data. Candidate GMMs are selected from those developed for shallow crustal regions such as Iran, Turkey, Japan, Europe and the Middle East, and the western United States. We made the evaluation database prospective to all candidate GMMs to assess their predictive capability. The evaluation database is composed of 643 records from 240 earthquakes with magnitudes ranging from 3.9 to 7.3 and Joyner–Boore distances up to 300 km. We implemented the log‐likelihood method of Scherbaum et al. (2009), the Euclidean distance‐based ranking proposed by Kale and Akkar (2013), and the multivariate logarithmic score of Mak et al. (2017) to evaluate the candidate models. We ranked GMMs by paying attention to the issue of score variability. To assess the score variability, we generated resampled datasets from the whole database using the cluster bootstrap technique and ranked models based on their relative performance among bootstrap samples. Overall, Sedaghati and Pezeshk (2017), Zafarani et al. (2018), and Farajpour et al. (2019) local models outperform remaining models considering the whole database over the entire frequency range. For high‐seismicity regions, the Zhao et al. (2006) model can be used in line with the first two local models to better quantify epistemic uncertainties associated with the process of model selection. In addition to aforementioned local models, Bindi et al. (2014) show acceptable performance against small‐to‐moderate magnitude data and may be considered for estimating seismic hazard in low‐seismicity regions of Iran.

Ground-motion simulation for the <i>M</i><sub>W</sub>6.1 Ludian earthquake on 3 August 2014 using the stochastic finite-fault method

The stochastic finite-fault simulation method was applied to synthesize the horizontal ground acceleration seismograms produced by the <i>M</i>_W6.1 Ludian earthquake on August 3, 2014. For this purpose, we produced first a total of 200 kinematic source models for the Ludian event, which are characterized by the heterogeneous slip on the conjugated ruptured fault and the slip-dependent spreading of the rupture front. The results indicated that the heterogeneous slip and the spatial extent of the ruptured fault play dominant roles in the spatial distribution of ground motions in the near-fault area. The peak ground accelerations (PGAs) and 5%-damped pseudospectral accelerations (PSAs) at periods shorter than 0.5 s estimated on the resulting synthetics generally match well with the observations at stations with Joyner-Boore distances (<i>R</i>_JB) greater than 20 km. The synthetic PGVs and PSAs at periods of 0.5 s and 0.75 s are in good agreement with predicted medians by the Yu14 model (Yu et al., 2014). However, the synthetic results are generally much lower than the predicted medians by BSSA14 model (Boore et al., 2014). Moreover, the ground motion variability caused by the randomness in the source rupture process was evaluated by these synthetics. The standard deviations of PSAs on the base-10 logarithmic scale, Sigma[log10(PSA)], are closely dependent on either the spectral period or the <i>R</i>_JB. The Sigma[log10(PSA)] remains a constant approximately 0.55 at periods shorter than 0.1 s, and then increase continuously up to ~0.13 as the period increases from 0.1 to 2.0 s. The Sigma[log10(PSA)] values at periods of 0.1‒2.0 s show the downward tendency as the <i>R</i>_JB values increase. However, the Sigma[log10(PSA)]​​​​​​​ values at periods shorter than 0.1 s decrease as the <i>R</i>_JB values increase up to ~50 km, and then increase with the increasing <i>R</i>_JB. Furthermore, we found that the ground-motion variability shows the significant dependence on the azimuth.

A Ground Motion Prediction Model for Average Spectral Acceleration

ABSTRACT This study presents a ground motion prediction model that directly estimates the median and dispersion of Saavg, defined as the geometric mean of 5%-damped pseudo-acceleration ordinates of oscillators with periods between one fifth and three times the structure’s period of vibration. This model is applicable for ground motions with moment magnitudes between 5 and 8 and Joyner-Boore distances between 0 km and 150 km. Results show that the dispersion of Saavg is lower than that of Sa(T1). A model to estimate the correlation between Saavg ordinates at different periods of vibration and between orthogonal components is also presented.

Ground Motion Prediction Model for the Peak Inelastic Displacement of Single-Degree-of-Freedom Bilinear Systems

This paper presents a ground motion prediction model (GMPM) for estimating medians and standard deviations of the random horizontal component of the peak inelastic displacement of 5% damped single-degree-of-freedom (SDOF) systems, with bilinear hysteretic behavior and 3% postelastic stiffness ratio, directly as a function of the earthquake magnitude and the distance to the source. The equations were developed using a mixed effects model, with 1,662 recorded ground motions from 63 seismic events. In the proposed model, the median is computed as a function of the vibration period and the normalized strength of the system, as well as the event magnitude and the Joyner-Boore distance to the source. The standard deviation of the model is computed as a function of the vibration period and the normalized strength of the system. The proposed model has the advantage of not requiring an auxiliary elastic GMPM to predict the median and dispersion of peak inelastic displacement.

The development of attenuation relationship for Northwest Anatolia region

Ground-motion attenuation relationships using the 1999 Kocaeli earthquake data were developed for the Northwest Anatolia region. This region is seismically active due to its location on Northwest Anatolia Fault Zone and was affected by the 1999 Kocaeli and Duzce earthquakes. Properties of the investigated stations and strong ground-motion data were taken from the Strong Ground Motion Database of Turkey (2017) (TR-NSMN) and Pacific Earthquake Engineering Research Center-Enhancement of Next Generation Attenuation Relationships for Western US (PEER-NGA-West2) database. SeismoSignal software was used in the evaluation of the acceleration records measured in the stations. A generated database for this study contains 369 mainshock and aftershock records, which occurred in the region of 39.39 to 41.03 North (N)/26.04 to 31.73 East (E) coordinates between the years of 1999 (Kocaeli earthquake) and 2006. In this research, peak ground acceleration is greater than 1 gal, and moment magnitude (M W ) is greater than 4.0 and Joyner-Boore distance (R JB ) is 1–344 km. These records were taken from 76 stations located in the investigation area. In addition to these data, 33 mainshock records worldwide were used for recovery of regression coefficients. Therefore, total of 402 data were used in this research. Attenuation relationships obtained from different types of ground were derived from the model generated by Boore et al. (Seismol Res Lett 68(1):128–153, 1997) for shallow earthquakes in North America. In this study, attenuation relation equations were developed by applying nonlinear regression analysis, with Statistical Package for the Social Sciences (SPSS) Statistics 20.0 software for B-C and D class soil according to the National Earthquake Hazards Reduction Program (NEHRP) classification system.