Acceleration Spectrum Intensity Research Articles

Ground-motion effects on liquefaction response

This article evaluates the influence of ground-motion characteristics on the liquefaction response of free-field level-ground deposits. Ground motions imposed on liquefiable soils have historically been characterized by the peak ground acceleration (PGA). In simplified procedures for liquefaction evaluation, the use of the ground surface PGA can be justified by the fact that it is closely related to the peak shear stresses developing in the critical zone for liquefaction manifestation, at shallow depths. In nonlinear dynamic analysis (NDA), however, such simplified characterization of the input motion using the bedrock-level PGA can result in large record-to-record variability in the computed response. Record-to-record variability can be substantially reduced by employing more appropriate ground-motion intensity measures (IMs) for specific aspects of the liquefaction response observed in NDA. Among 25 IMs examined in this study, the Modified Acceleration Spectrum Intensity (MASI), defined as the integral of the acceleration spectrum over periods 0.1–1.5 s, is found to be the most efficient IM for the prediction of the pore-pressure response of liquefiable deposits, whereas Velocity Spectrum Intensity (VSI) ranks among the best-performing IMs for response parameters related to ground deformations. Importantly, such “multiple-period spectrum IMs” are shown to perform consistently better than several highly-regarded time-integrated IMs (e.g. Arias intensity, CAV). Conclusions and recommendations are drawn on the basis of a comprehensive series of NDAs involving 180 input motions and 13 deposit models based on characteristic soil profiles from Christchurch.

Seismic fragility functions for earthquake-induced landslide risk assessment using identified optimal earthquake intensity measures

Seismic fragility analysis can relate the probability of unsatisfactory performance of slopes with increasing intensity of ground motions, which is the basic component of landslide hazard risk assessment. Determination of the optimal earthquake intensity measure (IM) is one of important prerequisite for seismic fragility analysis. Although a small number of studies have already performed seismic fragility analysis of slopes, the optimal IM for seismic fragility analysis of slopes have not been discussed and researched. In the present study, 15 IMs and two different engineering demand parameters (EDPs), including factor of safety (FOS) and Newmark permanent displacement (NPD), are selected for probabilistic seismic demand and seismic fragility analysis of slopes. The metrics of correlation, practicality, efficiency, and proficiency are adopted to identify the optimal earthquake IMs among the studied 15 IMs for two EDPs in seismic fragility analysis of slopes respectively. The results have found that the optimal IM is different for slope fragility analysis when different EDPs are selected. Acceleration spectrum intensity is the most optimal IM among the examined 15 IMs for seismic fragility analysis of slopes when FOS is adopted as the EDP. When NPD is selected as the EDP, root mean square of acceleration and velocity spectrum intensity are in general more appropriate than other IMs. In the last, the seismic fragility curves with regard to two EDPs and corresponding optimal IMs are derived for interpreting more properly slope seismic performance and earthquake-induced landslide risk.

Rapid damage state classification for underground box tunnels using machine learning

This study develops and compares the performance of eight machine learning (ML) models to rapidly predict the seismic damage state of underground box tunnels. Nonlinear time history analyses of 24 soil-tunnel configurations subject to 85 ground motions were performed to generate the dataset for the ML models. The aspect ratio, buried depth, flexibility ratio, and 23 ground motion intensity measures (IMs) are employed as input variables of ML models. The output variables are four damage states, namely ‘none’, ‘minor’, ‘moderate’, and ‘extensive’. Among the eight ML models, LightGBM is found to yield the most favorable prediction of the damage states, resulting in an accuracy of 91%. The effects of earthquake IMs were also examined. Results show that the spectral acceleration () and spectral displacement () at the fundamental period of the site (T 1) have the strongest correlation with the damage prediction. Finally, the effect of reducing the input variables to two groups (i.e. combinations of soil-tunnel configuration parameters with top five and top ten ranked IMs) on the model prediction capability was investigated. Accordingly, ), acceleration spectrum intensity, spectral velocity, and velocity spectrum intensity were identified as the key parameters representing the ground-motion characteristics needed for the predictive model.

Fuzzy inference system model for the spectrum site coefficients of the Türkiye Building Earthquake Code (2018)

The response spectra in the seismic design codes guide the seismic design force calculations that are crucial for structural safety and construction costs. In general, they are determined by crisp logic-based numerical classifications of seismic parameters, which primarily affect the shape and values of the spectrum. Crisp logic response spectra generation may have limitations in the accurate determination of relevant parameters. In this paper, a fuzzy inference system (FIS) rule-based model is proposed to address this issue. The proposed model uses spectral acceleration coefficients and shear wave velocity as inputs to generate the site coefficients of the response spectra according to the Türkiye Building Earthquake Code (TBEC 2018). The FIS model spectra generation is compared with the crisp logic model for thirty-five examples, and the model performance is evaluated. The study demonstrates significant differences between the two models in terms of the response spectra' shape and acceleration spectrum intensity values, but the FIS model provides comparatively better accuracy in response spectra generation. The proposed model can be modified and applied to various parameters for generating response spectra in different seismic design codes with the exposition of fuzzy logic rules that show the concerned problem's internal working mechanism.

Seismic response prediction using intensity measures: Graphite nuclear reactor core model case study

Seismic response analyses of structures have conventionally used the peak ground acceleration or spectral acceleration as an intensity measure to estimate the engineering demand parameters. An extensive shaking table test program was carried out on a quarter-sized advanced gas-cooled reactor (AGR) core model to investigate the global dynamic behavior of the system with degraded graphite components while subjected to seismic excitation. Evaluation of the most widely considered intensity measures, with respect to their capability for predicting the seismic response of an AGR core–like structure, is performed. Twenty intensity measures of 16 distinct seismic input motions are formulated and correlated, with experimental measurements describing the dynamic response of the reactor core model. Linear correlations are constructed for each intensity measure to statistically determine the best metric for predicting the seismic response of the AGR core model, and statistical analysis indicates that the acceleration spectrum intensity (ASI) is best suited to characterize and describe the structural demand of an AGR core-like structure when subjected to seismic loading. A response prediction tool is developed, based on empirically derived linear correlations, to estimate column distortions and determine the critical input motion for further experimental and numerical studies. Statistical analysis indicates that predicted column distortions, compared against direct experimental displacements, are significant, repeatable, and accurate.

Empirical Correlations Between Horizontal and Vertical Ground-Motion Intensity Measures

ABSTRACTThis study examined empirical correlations among several horizontal and vertical ground-motion intensity measures (IMs), including spectral acceleration (SA), peak ground acceleration (PGA), peak ground velocity, acceleration spectrum intensity, velocity spectrum intensity, displacement spectrum intensity, spectrum intensity, effective peak acceleration (EPA), effective peak velocity (EPV), and effective peak displacement (EPD). The theoretical basis for the prediction equations of EPA, EPV, and EPD were developed based on the ground-motion model (GMM) of SA(T). Horizontal and vertical Next Generation Attenuation (NGA)-West2 GMMs and associated ground motions from active shallow crustal earthquakes in the NGA-West2 database were used to calculate empirical correlations. Fisher ? transformation and nonparametric bootstrapping methods were able to accurately describe the uncertainty caused by the limited sample size. The multivariate normality of the total residuals of the horizontal and vertical ground-motion IMs was verified. The results have shown a moderate correlation between the same IMs of horizontal and vertical ground motions. The difference in correlations between the IMs for two different combination cases (IMi,H–IMj,V and IMj,H–IMi,V) was not significant. The trends of ρlnIMV,lnSAH and ρlnIMH,lnSAV were almost the same, except that ρlnIMV,lnSAH was greater than ρlnIMH,lnSAV in the 0–0.3 s period, except for ρlnPGAV,lnSAH. Moreover, the median correlation coefficients were parametrically fitted to establish a correlation coefficient prediction model. Finally, an example of constructing the conditional distribution using the correlation coefficient models for horizontal and vertical ground motions IMs was given. The correlation coefficient models by this study provide the theoretical basis for the selection of horizontal and vertical ground motions using generalized conditional intensity measure.

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.

Identification of optimal ground-motion intensity measures for assessing liquefaction triggering and lateral displacement of liquefiable sloping grounds

This article aims at identifying the optimal scalar- and vector-valued intensity measures (IMs) for predicting liquefaction triggering and the consequence of liquefaction (i.e. permanent deformation of sloping grounds), respectively. A total of 169 ground motions were selected from the NGA-West2 database. Using the selected ground motions as input, one-dimensional dynamic analyses were conducted for generic sloping ground soil profiles consisting of a loose-sand liquefiable layer implemented in OpenSees. The excess pore water pressure ratio and the liquefaction-induced lateral displacement were regarded as the engineering demand parameters (EDPs) of interest. A total of 20 scalar-IMs and 21 vector-IMs representative of various characteristics of seismic loading were evaluated as candidate IMs. The criteria for identifying optimal IMs include consideration for the efficiency, sufficiency, and predictability of the given IMs. An error propagation approach was employed to evalute the overall uncertainty of EDPs under scenario earthquakes using different IMs as predictor variables. Based on the results of extensive comparative analyses, acceleration spectrum intensity (ASI), and the vector of peak ground acceleration and spectral acceleration at 0.3 s (peak ground acceleration (PGA) and Sa(0.3 s), respectively) are identified as the optimal scalar- and vector-IM for liquefaction triggering evaluation, respectively. However, Arias intensity ( Ia) and vectors of [ Ia, cumulative absolute velocity] and [PGA, Ia] are identified as the optimal scalar- and vector-IM for predicting the liquefaction-induced lateral displacements. The optimal IMs identified could be used in performance-based liquefaction hazard evaluations, to assess the liquefaction triggering and consequence of liquefiable sites.

Factors Affecting Site-Specific Response Analysis

ABSTRACT The engineering purpose of a site-specific response analysis is to estimate the uniform hazard acceleration spectrum on the ground surface for a selected hazard level. One of the mandatory components for site response analyses is one or more representative acceleration time histories that need to be scaled with respect to the calculated seismic hazard level for the selected site. The selection and scaling procedures of earthquake acceleration records play an important role in this approach. The effects and differences in using two different scaling approaches are studied: scaling with respect to ground motion parameters and response spectrum scaling. A set of homogeneous ground motion prediction relationships are developed for peak ground acceleration, peak ground velocity, root-mean-square acceleration, Arias intensity, cumulative absolute velocity, maximum spectral acceleration, response spectrum intensity, and acceleration spectrum intensity based on a uniform set of acceleration records for ground motion parameter scaling. The uncertainties associated with site response analysis are considered as epistemic and aleatory uncertainties in source characteristics, soil profile, and soil properties. Aleatory variability is due to the intrinsic randomness of natural systems; it cannot be reduced with additional data (Passeri et al. 2020), however; its variability may be modeled by probability distribution functions. Thus, one possibility is to determine the probability distribution of the acceleration spectrum calculated on the ground surface for all possible input acceleration records, site profiles, and dynamic soil properties. The variability in the earthquake source and path effects are considered using a large number of acceleration records compatible with the site-dependent earthquake hazard in terms of fault mechanism, magnitude, and distance range recorded on stiff site conditions. Likewise, a large number of soil profiles may be considered to account for the site condition variability. The uncertainties related to dynamic soil properties may be considered as possible variability of maximum dynamic shear modulus in site response analyses. A methodology is proposed to estimate a uniform hazard acceleration spectrum on the ground surface based on the probabilistic assessment of the factors involved in site response analysis. The uniform hazard acceleration spectra obtained from a case study are compared with the spectra calculated by probabilistic models proposed in the literature.

A lateral load distribution for the static analysis of base-isolated building frames under the effect of far-fault and near-fault ground motions

This paper attempts to examine the effect of the scaling of ground motion records on the seismic responses of base-isolated buildings by using the three scaling methods including the ASCE 7–10, acceleration spectrum intensity, SIa, and the spectral acceleration corresponding to the effective period of the base-isolated structure at the design displacement, Sa(TD). The buildings had steel moment-resisting and X-braced systems and were isolated with lead rubber bearings (LRBs) at the base. Near-fault ground motions with Forward Directivity (FD), Fling-Step (FS) and No Pulse (No P.) characteristics as well as far-fault ground motion records were studied in this paper. The discrepancy in the seismic responses as well as the effect of the pulse period in the case of pulse-like ground motions was scrutinized for the three scaling methods. Also, the response spectrum analysis (RSA) and static method with the equivalent lateral force distribution prescribed in ASCE 7–10 were carried out. The results indicate that the RSA as well as the static analysis, prescribed in ASCE 7–10, underestimates the story shears of the base-isolated buildings. The underestimation increases in the case of the FF and No P. ground motions having a large amount of spectral acceleration in the higher modes region. Also, the underestimation increases with the increase in the height of the base-isolated buildings as well as in the case of the moment-resisting frames compared to the X-braced ones. Finally, by means of the results derived from the time history analyses, a formula was proposed to determine the lateral force distribution along the height of the base-isolated buildings with LRBs considering the characteristics of the isolator and the structure for different types of the ground motions.

Optimal Earthquake Intensity Measures for Probabilistic Seismic Demand Models of Base-Isolated Nuclear Power Plant Structures

The purpose of this study is to evaluate the optimal earthquake intensity measures (IMs) for probabilistic seismic demand models (PSDMs) of the base-isolated nuclear power plant (NPP) structures. The numerical model of NPP structures is developed using a lumped-mass stick model, in which a bilinear model is employed to simulate the force-displacement relations of base isolators. In this study, 20 different IMs are considered and 90 ground motion records are used to perform time-history analyses. The seismic engineering demand parameters (EDPs) are monitored in terms of maximum floor displacement (MFD), the maximum floor acceleration (MFA) of the structures, and maximum isolator displacement (MID). As a result, a set of PSDMs of the base-isolated structure is developed based on three EDPs (i.e., MFD, MFA, and MID) associated with 20 IMs. Four statistical parameters including the coefficient of determination, efficiency (i.e., standard deviation), practicality, and proficiency are then calculated to evaluate optimal IMs for seismic performances of the isolated NPP structures. The results reveal that the optimal IMs for PSDMs with respect to MFD and MID are velocity spectrum intensity, Housner intensity, peak ground velocity, and spectral velocity at the fundamental period. Meanwhile, peak ground acceleration, acceleration spectrum intensity, A95, effective peak acceleration, and sustained maximum acceleration are efficient IMs for PSDMs with respect to MFA of the base-isolated structures. On the other hand, cumulative absolute velocity is not recommended for determining the exceedance of the operating basis earthquake of base-isolated NPP structures.

Optimal earthquake intensity measures for probabilistic seismic demand models of ARP1400 reactor containment building

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R2), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

Seismic fragility analysis of the Koyna gravity dam with layered rock foundation considering tensile crack failure

In the present investigation, the seismic fragility analysis of the Koyna dam-reservoir-layered rock foundation system is performed, considering foundation flexibility. For material non-linearity, the Concrete Damaged Plasticity (CDP) model and Mohr-Coulomb failure model are adopted for dam and foundation, respectively. The finite element modelling takes into account the material flexibility, inertial, and damping properties. For the seismic analysis, ground motions are picked according to the Conditional Mean Spectrum approach. An Incremental Dynamic Analysis (IDA) method is used in which each ground motion is scaled at different intensity levels and directly these ground motions are adopted for the time-history analysis. The ground motion Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), and Acceleration Spectrum Intensity (ASI) are preferred as an intensity measure (IM) parameter. For the seismic fragility analysis, the tensile crack failure in the dam is considered as a limit state. Analytical fragility curves are plotted for the various vulnerability states of the gravity dam based on the damage indices which are evaluated using crack length and dissipation energy in the dam. Numerical results indicate that the dam with more flexible rock layers is more sensitive against seismic forces; however, the dam with hard rock layers is on the safer side. The crest displacement and heel stress can be viewed as a damage measure (DM) parameter for the IDA method. It is observed that the ground motion PGV shows a distinct result in IDA curves as compared to PGA and ASI. However, in fragility analysis, the seismic risk of a gravity dam can be evaluated better against PGA and ASI as compared to PGV.

SEISMIC INTENSITY MEASURES FOR THE DAMAGE EVALUATION OF CIRCULAR TUNNELS

The seismic intensity measure (IM) is a key parameter affecting the accuracy of seismic risk assessment, which plays an important role in the performance-based earthquake engineering framework. A reasonable IM can make the prediction of structural seismic responses more accurate. To study on seismic IMs which are suitable for the damage evaluation of circular tunnels, a two-dimensional finite element model was established for the nonlinear dynamic time history analyses of circular tunnel-surrounding rock interaction. The near-field ground motions without velocity pulses and far-field ground motions recommended by FEMA-P695 were used as the input in the numerical model. The overall lining damage indices in compression and in tension were used as the engineering damage measures to estimate the damage states of the lining. The applicability of 20 ground motion IMs commonly used in the engineering practice were investigated. The results show that based on the criteria of efficiency, practicality, proficiency and sufficiency, the best seismic IM for the damage evaluation of circular tunnels is the sustained maximum acceleration (SMA), and the second best is the acceleration spectrum intensity (ASI).

Effects of mainshock-aftershock sequences on fragility analysis of RC buildings with ageing

This paper presents the seismic vulnerability assessment of existing RC buildings designed according to previous non-seismic codes that are exposed to various levels of corrosion and mainshock-aftershock sequences. A refined finite element model of an existing four-storey reinforced concrete building is adopted. Twenty as-recorded natural ground motions are collected from international databases to perform incremental dynamic analyses for the inelastic response of the testbed building. The effects of corrosion are applied on external beams and columns to simulate a realistic exposure. The robust fragility assessment is conducted for a range of seismic intensity measures. Moreover, a new intensity measure, based on the modified acceleration spectrum intensity, is proposed. Such seismic parameter accounts for the elongation period experienced by structures during earthquake events and appears to be more reliable and accurate for corroded RC structures than the most adopted peak ground acceleration and spectral acceleration at the first natural period. The results of the comprehensive numerical simulations contribute to providing relevant indications on the non-linear response of existing corroded buildings under multiple excitations and, highlight that current seismic codes are no longer conservative for such detrimental phenomena.

Efficient Earthquake Intensity Measure for Seismic Vulnerability of Integral Abutment Bridges

The purpose of this study is to identify efficient earthquake intensity measures (IMs) for evaluating the seismic vulnerability of integral abutment bridges. A total of 90 ground motion records and 20 typical IMs were employed for the numerical analyses. A series of nonlinear time-history analyses was performed on the bridges to observe the lateral displacement of the bridge piers. Statistical parameters such as the coefficient of determination, standard deviation, and correlation coefficient were calculated to identify the strongly correlated IMs with the seismic performance of the bridges. The numerical results show that the efficient IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, and A95. Moreover, a set of fragility curves of the bridges was developed with respect to the efficient IMs.

Scalar- and vector-valued vulnerability analysis of shallow circular tunnel in soft soil

This paper presents a scalar- and vector-valued vulnerability analysis of shallow circular tunnel in soft soil. Numerous dynamic analyses were firstly performed to capture seismic response of the tunnel lining under transversal seismic shaking. Subsequently, a series of 15 intensity measures (IMs) are selected and tested to find the optimal IM used in the scalar-valued vulnerability analysis. The selected IMs are all tested based on their correlation, efficiency, practicality and proficiency, according to the regression analyses between the IMs and the damage measure (DM) for the examined tunnel. The peak ground acceleration (PGA) at the ground surface was demonstrated to be optimal IM, followed by peak ground velocity (PGV) and acceleration spectrum intensity (ASI). The scalar-valued vulnerability function was then developed in terms of optimal IM (PGA). Finally, the vulnerability functions based on vector-valued IMs were developed to obtain the exceeding probability of various damage states as a function of two IMs (PGA, ASI). This study reveals that the use of vector-valued IMs in the vulnerability analysis can significantly improve the correlation and efficiency with the seismic demand DM compared to the scalar-valued IM, thus reducing the uncertainties in evaluating earthquake risk. The scalar-valued vulnerability curves cannot represent the effect of a second IM on the seismic behavior of the tunnel, and it may either underestimate or overestimate the damage probability. Hence, the use of the second IM in vulnerability analysis and the development of vector-valued vulnerability functions lead to more proper evaluations of seismic risk.

Empirical Correlations between Generalized Ground-Motion Intensity Measures for Earthquakes in China

ABSTRACTThis study used earthquake records from China to investigate comprehensively the correlation coefficients between various intensity measures (IMs), including peak ground acceleration, peak ground velocity, spectral acceleration, spectrum intensity, acceleration spectrum intensity, Arias intensity, cumulative absolute velocity, and significant duration. After collection of metadata information, 681 three-component ground-motion recordings with magnitudes of Mw 4.9–6.9 were carefully processed and extracted from the China National Strong-Motion Observation Network System dataset (2007–2015). The applicability of both the Next Generation Attenuation (NGA)-West2 ground-motion model (GMM) and of other GMMs was verified for different IMs, regarding the China dataset. Then, empirical correlation coefficients between different IMs were computed, considering the uncertainty due to the different sample sizes of the observational data using the bootstrap sampling method and Fisher z transformation. Finally, the median values of the correlation coefficients were fitted as a continuous function of the vibration period in the range of 0.01–10.0 s and compared with the results of similar studies developed for shallow crustal regions worldwide. The developed region-specific correlation coefficient prediction model yielded tendencies approximately like those reported in other studies. However, obvious differences were found in long-period ranges of amplitude-based IMs, cumulative effect IMs, and significant duration. These results suggest the necessity of using region-specific correlation coefficients for generalized IMs in China. The presented results and parametric models could be easily implemented in a generalized IM ground-motion selection method or a vector-based probability seismic hazard analysis procedure for China.

Spectral acceleration matching procedure with respect to normalization approach

This study aimed at proposing a new ground motion scaling method for precise spectral matching between the response accelerations and the standard design spectrum regarding the normalization procedure. In this method, the dispersion in acceleration and displacement responses were decreased significantly. Moreover, 11 parameters were used for normalizing response accelerations, including peak ground acceleration, peak ground velocity, peak ground displacement, Arias intensity, Housner intensity, cumulative absolute velocity, maximum incremental velocity, energy index, acceleration spectrum intensity, velocity spectrum intensity, and specific energy density. Three sets of non-pulse-like, near-field pulse-like and non-pulse-like long-duration ground motions were taken into account to investigate the effect of earthquake characteristics on normalizing parameters. Hence, by performing sensitivity analysis, suitable parameters were determined for normalizing response accelerations. Statistical results illustrated that normalizing response accelerations to acceleration spectrum intensity, Housner intensity, and peak ground displacement led to minimum dispersion at acceleration-sensitive, velocity-sensitive, and displacement-sensitive regions, respectively. Moreover, the results showed that suitable normalizing parameters could be determined considering the period of vibration. It was concluded that normalizing response accelerations and scaling of them could lead to appropriate spectral matching and low dispersion. Finally, drift dispersion for four, eight, and twelve-story steel special concentrically braced frame structures under nonlinear fiber-element time-history analysis was evaluated carefully. The results indicated that the inter-story drift dispersion decreased acceptably in all structures.

Support Vector Regression for the Relationships between Ground Motion Parameters and Macroseismic Intensity in the Sichuan–Yunnan Region

In this paper, a nonlinear regression method called a support vector regression (SVR) is presented to establish the relationship between engineering ground motion parameters and macroseismic intensity (MSI). Sixteen ground motion parameters, including peak ground acceleration (PGA), peak ground velocity (PGV), Arias intensity, Housner intensity, acceleration spectrum intensity, velocity spectrum intensity, and others, are considered as candidates for feature selection to generate optimal SVR models. The datasets with both useable strong ground motion records and corresponding investigated MSIs in the Sichuan–Yunnan region, China, are all collected, and these 125 pairs of datasets are used for selecting features and comparing regression results. Nine ground motion parameters are selected as the most relevant features: PGA is the first fundamental one and PGV is the fifth relevant feature. Based on performance measures on the testing dataset, the best SVR model is given when the number of features is one all the way up to nine. According to predicted accuracy, SVR models with Gaussian kernel give much better MSI prediction than linear kernel SVR models and linear regression models. In particular, the Gaussian kernel SVR of PGA gives much higher MSI prediction accuracy than the linear regression model of PGV and PGA. The proposed SVR models are valid for MSI values from VI to IX, and they can be used for rapid mapping damage potential and reporting seismic intensity for this high-seismic-activity region.