Journal articles: 'Stochastic ground motion model'

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JACOB, C., K. SEPAHVAND, V. A. MATSAGAR, and S. MARBURG. "STOCHASTIC SEISMIC RESPONSE OF BASE-ISOLATED BUILDINGS." International Journal of Applied Mechanics 05, no. 01 (March 2013): 1350006. http://dx.doi.org/10.1142/s1758825113500063.

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The stochastic response of base-isolated building considering the uncertainty in the characteristics of the earthquakes is investigated. For this purpose, a probabilistic ground motion model, for generating artificial earthquakes is developed. The model is based upon a stochastic ground motion model which has separable amplitude and spectral non-stationarities. An extensive database of recorded earthquake ground motions is created. The set of parameters required by the stochastic ground motion model to depict a particular ground motion is evaluated for all the ground motions in the database. Probability distributions are created for all the parameters. Using Monte Carlo (MC) simulations, the set of parameters required by the stochastic ground motion model to simulate ground motions is obtained from the distributions and ground motions. Further, the bilinear model of the isolator described by its characteristic strength, post-yield stiffness and yield displacement is used, and the stochastic response is determined by using an ensemble of generated earthquakes. A parametric study is conducted for the various characteristics of the isolator. This study presents an approach for stochastic seismic response analysis of base-isolated building considering the uncertainty involved in the earthquake ground motion.

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Edwards, Benjamin, and Donat Fäh. "A Stochastic Ground‐Motion Model for Switzerland." Bulletin of the Seismological Society of America 103, no. 1 (February 2013): 78–98. http://dx.doi.org/10.1785/0120110331.

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Cui, Xi Zhong, Yong Xu Liu, and Han Ping Hong. "A Stochastic Model for Simulating Vertical Pulseless Near-Fault Seismic Ground Motions." Bulletin of the Seismological Society of America 112, no. 2 (December 7, 2021): 961–77. http://dx.doi.org/10.1785/0120210114.

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ABSTRACT The vertical near-fault seismic ground-motion component can cause significant structural deformation and damage, which can be evaluated from time history analysis using actual or synthetic ground-motion records. In this study, we propose a new stochastic model for the vertical pulseless near-fault ground motions that depends on earthquake magnitude, rupture distance, and site condition. The proposed model is developed based on the time–frequency characteristics of 606 selected actual vertical record components in strike-slip earthquakes. The use and validation of the model are presented using simulated records obtained by two simulation techniques. For the validation, the statistics of time–frequency-dependent power spectral acceleration estimated from the simulated records using the proposed stochastic model are compared with those from the actual records and the ground-motion models available in the literature.

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Wang, Zhi Hua, and Chong Shi Gu. "A New Non-Stationary Stochastic Seismic Ground Motion Model and its Application." Advanced Materials Research 243-249 (May 2011): 4627–33. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.4627.

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Considering the uncertainty and the time variation of frequency contents of real seismic excitation, a new versatile stochastic strong ground motion model named general stochastic seismic ground motion (GSSGM) model is presented in this paper. Some essential assumptions for the earthquake process used in this paper are first given. The intensity and energy of the target seismic ground motion are used to determine the model parameters. The frequency contents are demanded to be agreed with the main characteristics of the target ground motions. The GSSGM model is appropriate to simulate the stationary, intensity non-stationary and fully non-stationary stochastic processes. Additionally, a simple non-stationary stochastic seismic response analysis procedure based on the GSSGM model and the pseudo excitation theory is put forward. The presented non-stationary stochastic seismic response analysis procedure is later applied in the seismic response analysis of a real homogeneous earth dam. The non-stationary analysis results display the effects of non-stationarity on the seismic response of the dam and reflect the main phenomena of dynamic embankment-foundation interaction. The results indicate that the GSSGM model and the presented analysis procedure are effective.

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Lekshmy, P. R., and S. T. G. Raghukanth. "Stochastic earthquake source model for ground motion simulation." Earthquake Engineering and Engineering Vibration 18, no. 1 (January 2019): 1–34. http://dx.doi.org/10.1007/s11803-019-0487-8.

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Poulos, Alan, Eduardo Miranda, and Jack W. Baker. "Evaluation of Earthquake Response Spectra Directionality Using Stochastic Simulations." Bulletin of the Seismological Society of America 112, no. 1 (October 26, 2021): 307–15. http://dx.doi.org/10.1785/0120210101.

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ABSTRACT For earthquake-resistant design purposes, ground-motion intensity is usually characterized using response spectra. The amplitude of response spectral ordinates of horizontal components varies significantly with changes in orientation. This change in intensity with orientation is commonly known as ground-motion directionality. Although this directionality has been attributed to several factors, such as topographic irregularities, near-fault effects, and local geologic heterogeneities, the mechanism behind this phenomenon is still not well understood. This work studies the directionality characteristics of earthquake ground-motion intensity using synthetic ground motions and compares their directionality to that of recorded ground motions. The two principal components of horizontal acceleration are sampled independently using a stochastic model based on finite-duration time-modulated filtered Gaussian white-noise processes. By using the same stochastic process to sample both horizontal components of motion, the variance of horizontal ground acceleration has negligible orientation dependence. However, these simulations’ response spectral ordinates present directionality levels comparable to those found in real ground motions. It is shown that the directionality of the simulated ground motions changes for each realization of the stochastic process and is a consequence of the duration being finite. Simulated ground motions also present similar directionality trends to recorded earthquake ground motions, such as the increase of average directionality with increasing period of vibration and decrease with increasing significant duration. These results suggest that most of the orientation dependence of horizontal response spectra is primarily explained by the finite significant duration of earthquake ground motion causing inherent randomness in response spectra, rather than by some physical mechanism causing polarization of shaking.

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Atkinson, Gail M. "A Comparison of Eastern North American ground Motion Observations with Theoretical Predictions." Seismological Research Letters 61, no. 3-4 (July 1, 1990): 171–80. http://dx.doi.org/10.1785/gssrl.61.3-4.171.

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Abstract Theoretical predictions of eastern North American (ENA) ground motion parameters based on a stochastic model (Boore and Atkinson, 1987; Atkinson and Boore, 1990) are evaluated in light of recent data, including data from the 1988 Saguenay, Quebec earthquake. The evaluation is based on visual comparisons of predicted and observed ground motion amplitudes, and on regression analyses of the data. Data are consistent with the theoretical model on average, although high-frequency ground motions from the Saguenay earthquake are underpredicted. It is hypothesized that differences between the observations and the stochastic model predictions may be explained by the presence of two corner frequencies in the source spectrum. Any single earthquake may exhibit ground motions significantly higher or lower than predicted due to local or earthquake-specific effects not accounted for in predictions of ‘average’ motions.

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Sabetta, Fabio, Antonio Pugliese, Gabriele Fiorentino, Giovanni Lanzano, and Lucia Luzi. "Simulation of non-stationary stochastic ground motions based on recent Italian earthquakes." Bulletin of Earthquake Engineering 19, no. 9 (April 7, 2021): 3287–315. http://dx.doi.org/10.1007/s10518-021-01077-1.

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AbstractThis work presents an up-to-date model for the simulation of non-stationary ground motions, including several novelties compared to the original study of Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996). The selection of the input motion in the framework of earthquake engineering has become progressively more important with the growing use of nonlinear dynamic analyses. Regardless of the increasing availability of large strong motion databases, ground motion records are not always available for a given earthquake scenario and site condition, requiring the adoption of simulated time series. Among the different techniques for the generation of ground motion records, we focused on the methods based on stochastic simulations, considering the time- frequency decomposition of the seismic ground motion. We updated the non-stationary stochastic model initially developed in Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996) and later modified by Pousse et al. (Bull Seism Soc Am 96:2103–2117, 2006) and Laurendeau et al. (Nonstationary stochastic simulation of strong ground-motion time histories: application to the Japanese database. 15 WCEE Lisbon, 2012). The model is based on the S-transform that implicitly considers both the amplitude and frequency modulation. The four model parameters required for the simulation are: Arias intensity, significant duration, central frequency, and frequency bandwidth. They were obtained from an empirical ground motion model calibrated using the accelerometric records included in the updated Italian strong-motion database ITACA. The simulated accelerograms show a good match with the ground motion model prediction of several amplitude and frequency measures, such as Arias intensity, peak acceleration, peak velocity, Fourier spectra, and response spectra.

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Kiremidjian, Anne S., and Shigeru Suzuki. "A stochastic model for site ground motions from temporally dependent earthquakes." Bulletin of the Seismological Society of America 77, no. 4 (August 1, 1987): 1110–26. http://dx.doi.org/10.1785/bssa0770041110.

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Abstract A stochastic model is presented for estimating probabilities of exceeding site ground motions due to temporally dependent earthquake events. The model reflects the hypothesized dependence of the size of large earthquake events on the time of occurrence of the last major earthquake. An empirical attenuation relationship is used to describe the ground motion at a site originating from a well-defined fault system. The application of the model to the Middle America Trench is discussed. The seismic hazard potential in Mexico City is computed in terms of probabilities of exceeding peak ground acceleration levels. The results indicate that consideration of the seismic gap is important for estimating the seismic hazard at a site. It is also observed that site hazard estimates are greatly dependent on the specific attenuation relationship used. The need for other approaches of ground motion estimation is recognized.

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Yamamoto, Y., and J. W. Baker. "Stochastic Model for Earthquake Ground Motion Using Wavelet Packets." Bulletin of the Seismological Society of America 103, no. 6 (October 22, 2013): 3044–56. http://dx.doi.org/10.1785/0120120312.

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Harada, Takanori. "A STOCHASTIC SH WAVE MODEL OF EARTHQUAKE GROUND MOTION." Doboku Gakkai Ronbunshu, no. 495 (1994): 43–50. http://dx.doi.org/10.2208/jscej.1994.495_43.

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Medel-Vera, Carlos, and Tianjian Ji. "A stochastic ground motion accelerogram model for Northwest Europe." Soil Dynamics and Earthquake Engineering 82 (March 2016): 170–95. http://dx.doi.org/10.1016/j.soildyn.2015.12.012.

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Cacciola, P., and A. Tombari. "A stochastic ground motion model for the urban environment." Probabilistic Engineering Mechanics 59 (January 2020): 103026. http://dx.doi.org/10.1016/j.probengmech.2020.103026.

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14

Naguit, Muriel, Phil Cummins, Mark Edwards, Hadi Ghasemi, Bartolome Bautista, Hyeuk Ryu, and Marcus Haynes. "From Source to Building Fragility: Post-Event Assessment of the 2013 M7.1 Bohol, Philippines, Earthquake." Earthquake Spectra 33, no. 3 (August 2017): 999–1027. http://dx.doi.org/10.1193/0101716eqs173m.

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We use ground-motion simulations of the 2013 Bohol, Philippines, earthquake along with a new post-disaster exposure/damage database to constrain building fragility and vulnerability. The large number of damaged buildings (>70,000) and the wide spread of seismic intensities caused by this earthquake make it an ideal candidate for such a study. An extensive survey was conducted leading to a robust description of over 25,000 damaged and undamaged structures. Ground-motion fields were simulated using ground-motion prediction equations and stochastic modeling, and the estimated and observed values were compared. The finite source model used in the simulation was based on the analysis of aftershocks and SAR data. The ground motions were associated with the empirical database to derive fragility and vulnerability models. Results indicate that the pattern of damage is best captured in the stochastic simulation. Constraints were placed on seismic building fragility and vulnerability models, which can promote more effective implementation of construction regulations and practices.

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Sangeetha, S., and S. T. G. Raghukanth. "Stochastic Source Model for Strong Motion Prediction." International Journal of Geotechnical Earthquake Engineering 9, no. 2 (July 2018): 1–22. http://dx.doi.org/10.4018/ijgee.2018070101.

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The article aims at developing a stochastic model which simulates spatial distribution of slip on the fault plane. This is achieved by analysing a large dataset of 303 finite-fault rupture models from 152 past earthquakes with varying fault mechanisms and in the magnitude range of 4.11-9.12. New scaling relations to predict the seismic source parameters such as fault length, fault width, rupture area, mean and standard deviation of slip have been derived for distinct fault mechanisms. The developed methodology models the spatial variability of slip as a two-dimensional von Karman power spectral density function (PSD) and correlation lengths are estimated. The proposed stochastic slip model is validated by comparing the simulated near-field ground response with the recorded data available for the 20th September 1999 Chi-Chi earthquake, Taiwan.

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Shinozuka, M., and G. Deodatis. "Stochastic process models for earthquake ground motion." Probabilistic Engineering Mechanics 3, no. 3 (September 1988): 114–23. http://dx.doi.org/10.1016/0266-8920(88)90023-9.

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Tsioulou, Alexandra, Alexandros A. Taflanidis, and Carmine Galasso. "Validation of stochastic ground motion model modification by comparison to seismic demand of recorded ground motions." Bulletin of Earthquake Engineering 17, no. 6 (February 7, 2019): 2871–98. http://dx.doi.org/10.1007/s10518-019-00571-x.

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Miao, Huiquan, Yanqiong Ding, and Jiaxu Shen. "Stochastic Semi-Physical Model for Nonstationary Spatially Variable Ground Motions in an Engineering Site." Buildings 12, no. 10 (October 18, 2022): 1727. http://dx.doi.org/10.3390/buildings12101727.

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Spatially variable ground motions are crucial for the seismic analysis and design of extended and multi-support structures. In this study, a new random nonstationary spatially variable ground motion model based on the propagation process of seismic waves is proposed. In particular, the amplitude and phase transfer functions of seismic waves at the local site are studied herein. The probability density function of the corresponding parameters is given. Two simple examples are used to show the generation of random ground motions. Compared with traditional methods, our proposed model not only has a clear physical background but also shows good practicability. The model should be for those researchers who want to use nonstationary spatially variable ground motions to study the seismic response of lifeline systems or building portfolios.

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Vetter, Christopher R., Alexandros A. Taflanidis, and George P. Mavroeidis. "Tuning of stochastic ground motion models for compatibility with ground motion prediction equations." Earthquake Engineering & Structural Dynamics 45, no. 6 (December 29, 2015): 893–912. http://dx.doi.org/10.1002/eqe.2690.

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Hartzell, Stephen, Stephen Harmsen, Arthur Frankel, and Shawn Larsen. "Calculation of broadband time histories of ground motion: Comparison of methods and validation using strong-ground motion from the 1994 Northridge earthquake." Bulletin of the Seismological Society of America 89, no. 6 (December 1, 1999): 1484–504. http://dx.doi.org/10.1785/bssa0890061484.

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Abstract This article compares techniques for calculating broadband time histories of ground motion in the near field of a finite fault by comparing synthetics with the strong-motion data set for the 1994 Northridge earthquake. Based on this comparison, a preferred methodology is presented. Ground-motion-simulation techniques are divided into two general methods: kinematic- and composite-fault models. Green's functions of three types are evaluated: stochastic, empirical, and theoretical. A hybrid scheme is found to give the best fit to the Northridge data. Low frequencies (< 1 Hz) are calculated using a kinematic-fault model and a 3D finite-difference code to propagate energy through a realistic 3D velocity structure. High frequencies (> 1 Hz) are calculated using a composite-fault model with a fractal subevent size distribution and stochastic, bandlimited, white-noise Green's functions. At frequencies below 1 Hz, theoretical elastic-wave-propagation synthetics introduce proper seismic-phase arrivals of body waves and surface waves. The 3D velocity structure more accurately reproduces record durations for the deep sedimentary basin structures found in the Los Angeles region. At frequencies above 1 Hz, scattering effects become important and wave propagation is more accurately represented by stochastic Green's functions. A fractal subevent size distribution for the composite fault model ensures an ω−2 spectral shape over the entire frequency band considered (0.1-20 Hz).

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Atkinson, Gail M., and David M. Boore. "Ground-motion relations for eastern North America." Bulletin of the Seismological Society of America 85, no. 1 (February 1, 1995): 17–30. http://dx.doi.org/10.1785/bssa0850010017.

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Abstract Predictive relations are developed for ground motions from eastern North American earthquakes of 4.0 ≦ M ≦ 7.25 at distances of 10 ≦ R ≦ 500 km. The predicted parameters are response spectra at frequencies of 0.5 to 20 Hz, and peak ground acceleration and velocity. The predictions are derived from an empirically based stochastic ground-motion model. The relations differ from previous work in the improved empirical definition of input parameters and empirical validation of results. The relations are in demonstrable agreement with ground motions from earthquakes of M 4 to 5. There are insufficient data to adequately judge the relations at larger magnitudes, although they are consistent with data from the Saguenay (M 5.8) and Nahanni (M 6.8) earthquakes. The underlying model parameters are constrained by empirical data for events as large as M 6.8.

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Atkinson, Gail M., and David M. Boore. "Recent Trends in Ground Motion and Spectral Response Relations for North America." Earthquake Spectra 6, no. 1 (February 1990): 15–35. http://dx.doi.org/10.1193/1.1585556.

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Recent ground motion relations which predict pga, pgv and psrv for rock sites in ENA are based on a stochastic model whose parameters are indicated by seismological studies of earthquake source and attenuation processes. The validity of the model is verified by application to WNA. The choice of model parameters is validated by comparison of model predictions with ground motion data for ENA. For any magnitude, near-source ENA ground motions are enriched in high frequencies relative to WNA motions. This causes eastern pga values, and psrv values for frequencies greater than 10 Hz, to be greater than their western counterparts. For psrv at frequencies less than 10 Hz, median near-source ground motions in ENA are roughly comparable to those in WNA. Eastern ground motion characteristics have important implications for seismic hazard. High frequency structures in many parts of ENA face a hazard comparable to that in many active areas of California, whereas the hazard for low-frequency structures on rock sites in ENA is relatively modest.

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Tang, Yuxiang. "An Updated Corner-Frequency Model for Stochastic Finite-Fault Ground-Motion Simulation." Bulletin of the Seismological Society of America 112, no. 2 (January 18, 2022): 921–38. http://dx.doi.org/10.1785/0120210205.

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ABSTRACT Stochastic finite-fault ground-motion simulation is widely used in various scientific and engineering applications. However, the current theoretical modeling of the corner frequency used in the source spectrum model is problematic as it does not consider the impact of rupture velocity. This article provides a modification of the current corner-frequency modeling and establishes a correlation between corner frequency and rupture velocity, making the source spectrum model more theoretically consistent. An additional inspection of the source-duration model is provided, and the appropriateness of the application of the widely used 1/f0 source-duration model is discussed. A detailed comparison between the updated corner-frequency model and the currently used model (embodied in EXSIM) is provided for various magnitudes. For validation purposes, the updated corner-frequency and source-duration model is applied to predict the ground motions on rock sites during the 2012 ML 5.4 Moe earthquake that occurred in southeastern Australia and the 2014 Ms 6.5 Ludian earthquake that occurred in southwestern China. The results show that the updated model is reliable for providing more accurate estimates of corner frequency, source duration, and ground-motion amplitudes with smaller average residuals than the currently used model.

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Murzea, Patricia-Florina. "Calibration of the Ground Motion Model Using a Simplified Stochastic Model in the Case of the Central Exhibition Pavilion ROMEXPO." Applied Mechanics and Materials 430 (September 2013): 335–41. http://dx.doi.org/10.4028/www.scientific.net/amm.430.335.

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The aim of the paper is to present the results of applying the formulae of a simplified stochastic model for the calibration of some macroscopic parameters of the ground motion, on the basis of rather rough estimates. For this purpose the basic records combinations results obtained with the aid of computer programs (DaisyLab and LABView) are used, after digital recordings on the large span and rather isolated structure of the ROMEXPO Pavilion in Bucharest were performed. A stochastic model of stationary, low intensity, ground motion (referred to in literature as microtremors or ambient vibrations) was proposed by H. Sandi (1982, 2005). This lay at the basis of the specification of input for a consistent analysis of 3D earthquake induced motion of structures, adopted in the Romanian earthquake resistant design codes.

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Wang, Min, and Tsuyoshi Takada. "Macrospatial Correlation Model of Seismic Ground Motions." Earthquake Spectra 21, no. 4 (November 2005): 1137–56. http://dx.doi.org/10.1193/1.2083887.

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It is very important to estimate a macrospatial correlation of seismic ground motion intensities for earthquake damage predictions, building portfolio analyses etc., whereby damage in different locations has to be taken into account simultaneously. This study focuses on spatial correlation of the residual value between an observed and a predicted ground motion intensity, which is estimated by an empirical mean attenuation relationship. The residual value is modeled in such a way that the joint probability density function (PDF) of seismic ground-motion intensity can be characterized by the spatial correlation model as well as an empirical mean attenuation relationship, assuming that it constitutes a homogeneous two-dimensional stochastic field. Using the dense observation data of earthquakes that occurred in Japan and Taiwan in recent years, the macrospatial correlation model is proposed and the assumption of homogeneity is verified in this paper.

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Wong, Ivan G., Walter J. Silva, Robert Darragh, Nick Gregor, and Mark Dober. "A Ground Motion Prediction Model for Deep Earthquakes beneath the Island of Hawaii." Earthquake Spectra 31, no. 3 (August 2015): 1763–88. http://dx.doi.org/10.1193/012012eqs015m.

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Until recently, no ground motion prediction model was available for deep ( >20 km) Hawaiian earthquakes, including the 2006 M6.7 Kiholo Bay earthquake. We developed such a model based on the stochastic point-source model. Strong motion data from the 2006 event and 15 other deep Hawaiian earthquakes of M3.3 to M6.2 were inverted using a nonlinear least-squares inversion of Fourier amplitude spectra to estimate stress drops for input into the stochastic modeling and for the few larger events (M ≥ 5.0), to calibrate the ground motion prediction model. The ground motion model is valid for M3.5 to M7.5 over the Joyner-Boore ( RJB) distance range of 20 km to 400 km and are for 5%-damped horizontal spectral acceleration at 27 periods from PGA (0.01 s) to 10.0 s. The shallow site condition assumed for the model is soil and weathered basalt with a mean VS30 of 428 m/s.

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Pang, Rui, and Laifu Song. "Stochastic Dynamic Response Analysis of the 3D Slopes of Rockfill Dams Based on the Coupling Randomness of Strength Parameters and Seismic Ground Motion." Mathematics 9, no. 24 (December 15, 2021): 3256. http://dx.doi.org/10.3390/math9243256.

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Because rockfill strength and seismic ground motion are dominant factors affecting the slope stability of rockfill dams, it is very important to accurately characterize the distribution of rockfill strength parameters, develop a stochastic ground motion model suitable for rockfill dam engineering, and effectively couple strength parameters and seismic ground motion to precisely evaluate the dynamic reliability of the three-dimensional (3D) slope stability of rockfill dams. In this study, a joint probability distribution model for rockfill strength based on the copula function and a stochastic ground motion model based on the improved Clough-Penzien spectral model were built; the strength parameters and the seismic ground motion were coupled using the GF-discrepancy method, a method for the analysis of dynamic reliability of the 3D slope stability of rockfill dams was proposed based on the generalized probability density evolution method (GPDEM), and the effectiveness of the proposed method was verified. Moreover, the effect of different joint distribution models on the dynamic reliability of the slope stability of rockfill dams was revealed, the effect of the copula function type on the dynamic reliability of the slope stability was analysed, and the differences in the dynamic reliability of the slope stability under parameter randomness, seismic ground motion randomness, and coupling randomness of parameters and seismic ground motion were systematically determined. The results were as follows: the traditional joint distribution models ignored related nonnormal distribution characteristics of rockfill strength parameters, which led to excessively low calculated failure probabilities and overestimations of the reliability of the slope stability; in practice, we found that the optimal copula function should be selected to build the joint probability distribution model, and seismic ground motion randomness must be addressed in addition to parameter randomness.

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Tang, Yuxiang, Nelson Lam, Hing-Ho Tsang, and Elisa Lumantarna. "Use of Macroseismic Intensity Data to Validate a Regionally Adjustable Ground Motion Prediction Model." Geosciences 9, no. 10 (September 30, 2019): 422. http://dx.doi.org/10.3390/geosciences9100422.

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In low-to-moderate seismicity (intraplate) regions where locally recorded strong motion data are too scare for conventional regression analysis, stochastic simulations based on seismological modelling have often been used to predict ground motions of future earthquakes. This modelling methodology has been practised in Central and Eastern North America (CENA) for decades. It is cautioned that ground motion prediction equations (GMPE) that have been developed for use in CENA might not always be suited for use in another intraplate region because of differences in the crustal structure. This paper introduces a regionally adjustable GMPE, known as the component attenuation model (CAM), by which a diversity of crustal conditions can be covered in one model. Input parameters into CAM have been configured in the same manner as a seismological model, as both types of models are based on decoupling the spectral properties of earthquake ground motions into a generic source factor and a regionally specific path factor (including anelastic and geometric attenuation factors) along with a crustal factor. Unlike seismological modelling, CAM is essentially a GMPE that can be adapted readily for use in different regions (or different areas within a region) without the need of undertaking any stochastic simulations, providing that parameters characterising the crustal structure have been identified. In addressing the challenge of validating a GMPE for use in an area where instrumental data are scarce, modified Mercalli intensity (MMI) data inferred from peak ground velocity values predicted by CAM are compared with records of MMI of past earthquake events, as reported in historical archives. South-Eastern Australia (SEA) and South-Eastern China (SEC) are the two study regions used in this article for demonstrating the viability of CAM as a ground motion prediction tool in an intraplate environment.

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Atkinson, Gail M., and Paul G. Somerville. "Calibration of time history simulation methods." Bulletin of the Seismological Society of America 84, no. 2 (April 1, 1994): 400–414. http://dx.doi.org/10.1785/bssa0840020400.

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Abstract Ground-motion time histories for use in engineering analyses of structures in eastern North America are often simulated from seismological models, owing to the paucity of real recordings in the magnitude and distance ranges of interest. Two simulation methods have been widely used in recent years: the stochastic method and the ray-theory method. In the stochastic method, as implemented in this study, ground motion is treated as filtered Gaussian noise whose underlying spectrum is determined from an empirical region-specific seismological model of the source and propagation processes. In the ray-theory method, as implemented in this study, the ground motions are simulated by convolving an empirical source function with theoretical Green's functions for a specified crustal structure model. This article compares results of the two simulation methods for four well-recorded “calibration” events and assesses the applicability of the methods. The assessment is based on comparisons of ground-motion parameters from the simulated data with those of the actual recordings. Ground-motion parameters in the frequency range from 1 to 10 Hz are satisfactorily predicted by both methods. Averaged over the four events studied, the stochastic method underpredicts 1-Hz response spectra by 20 to 40% but accurately predicts response spectra for frequencies of greater than 2 Hz; it also accurately predicts peak ground acceleration and velocity. The wave-propagation method underpredicts 1-Hz response spectra by 10 to 40% but accurately predicts response spectra for higher frequencies; it overpredicts peak ground acceleration and velocity by 10 to 40%. Both methods are imprecise: the standard error of an estimate is a factor of about 2.2. The bias and standard error of an estimate for the wave-propagation method are generally slightly lower than for the stochastic method, if the focal depth of the event can be specified (i.e., as for a past earthquake). If the focal depth of the event is not known (i.e., as for a future earthquake) then the accuracy and precision of the two methods are about the same. The chief advantage of the wave-propagation method is its predictive power; since its attenuation function is derived from the focal depth and crustal structure it does not require knowledge of the empirical attenuation function. The chief advantage of the stochastic model is its economy and simplicity.

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Tsioulou, Alexandra, Alexandros A. Taflanidis, and Carmine Galasso. "Hazard-compatible modification of stochastic ground motion models." Earthquake Engineering & Structural Dynamics 47, no. 8 (April 17, 2018): 1774–98. http://dx.doi.org/10.1002/eqe.3044.

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Rietbrock, Andreas, Fleur Strasser, and Benjamin Edwards. "A Stochastic Earthquake Ground‐Motion Prediction Model for the United Kingdom." Bulletin of the Seismological Society of America 103, no. 1 (February 2013): 57–77. http://dx.doi.org/10.1785/0120110231.

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TAMURA, Keiichi, and Koh AIZAWA. "DIFFERENTIAL GROUND MOTION ESTIMATION USING A TIME-SPACE STOCHASTIC PROCESS MODEL." Doboku Gakkai Ronbunshu, no. 441 (1992): 49–55. http://dx.doi.org/10.2208/jscej.1992.49.

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Liao, Zhen-Peng, and Xing Jin. "A stochastic model of the Fourier phase of strong ground motion." Acta Seismologica Sinica 8, no. 3 (August 1995): 435–46. http://dx.doi.org/10.1007/bf02650572.

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Rezaeian, Sanaz, and Armen Der Kiureghian. "A stochastic ground motion model with separable temporal and spectral nonstationarities." Earthquake Engineering & Structural Dynamics 37, no. 13 (October 25, 2008): 1565–84. http://dx.doi.org/10.1002/eqe.831.

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Chen, Huiguo, Yingmin Li, and Junru Ren. "Fully Nonstationary Spatially Variable Ground Motion Simulations Based on a Time-Varying Power Spectrum Model." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/293182.

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By analyzing the evolutionary spectrum method for multivariate nonstationary stochastic processes, a simulation method for fully nonstationary spatially variable ground motion is proposed based on the Kameda time-varying power spectrum model. This method can properly simulate nonstationary spatially variable ground motion based on a target response spectrum. Two numerical examples, in which the Kameda time-varying power spectra are calculated for different conditions, are presented to demonstrate the capabilities of the proposed method. In the first example, the nonstationary spatially variable ground motion that satisfies the time-frequency characteristics and response characteristics of the original ground motion is simulated by identifying the parameters of the given time-varying power spectrum. In the second example, the ground motion that satisfies the design response spectra is simulated by defining the parameters of the time-varying power spectrum directly. The results demonstrate that the method can effectively simulate nonstationary spatially variable ground motion, which implies that the proposed method can be used in engineering applications.

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Kamae, Katsuhiro, Kojiro Irikura, and Arben Pitarka. "A technique for simulating strong ground motion using hybrid Green's function." Bulletin of the Seismological Society of America 88, no. 2 (April 1, 1998): 357–67. http://dx.doi.org/10.1785/bssa0880020357.

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Abstract A method for simulating strong ground motion for a large earthquake based on synthetic Green's function is presented. We use the synthetic motions of a small event as Green's functions instead of observed records of small events. Ground motions from small events are calculated using a hybrid scheme combining deterministic and stochastic approaches. The long-period motions from the small events are deterministically calculated using the 3D finite-difference method, whereas the high-frequency motions from them are stochastically simulated using Boore's method. The small-event motions are synthesized summing the long-period and short-period motions after passing them through a pair of matched filters to follow the omega-squared source model. We call the resultant time series “hybrid Green's functions” (HGF). Ground motions from a large earthquake are simulated by following the empirical Green's function (EGF) method. We demonstrate the effectiveness of the method at simulating ground motion from the 1995 Hyogo-ken Nanbu earthquake (Mw 6.9).

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Hacıefendioğlu, K. "Deconvolution effect of near-fault earthquake ground motions on stochastic dynamic response of tunnel-soil deposit interaction systems." Natural Hazards and Earth System Sciences 12, no. 4 (April 24, 2012): 1151–57. http://dx.doi.org/10.5194/nhess-12-1151-2012.

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Abstract. The deconvolution effect of the near-fault earthquake ground motions on the stochastic dynamic response of tunnel-soil deposit interaction systems are investigated by using the finite element method. Two different earthquake input mechanisms are used to consider the deconvolution effects in the analyses: the standard rigid-base input and the deconvolved-base-rock input model. The Bolu tunnel in Turkey is chosen as a numerical example. As near-fault ground motions, 1999 Kocaeli earthquake ground motion is selected. The interface finite elements are used between tunnel and soil deposit. The mean of maximum values of quasi-static, dynamic and total responses obtained from the two input models are compared with each other.

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Lee, Ya-Ting, Kuo-Fong Ma, Ming-Che Hsieh, Yin-Tung Yen, and Yu-Sheng Sun. "Synthetic Ground-Motion Simulation Using a Spatial Stochastic Model with Slip Self-Similarity: Toward Near-Source Ground-Motion Validation." Terrestrial, Atmospheric and Oceanic Sciences 27, no. 3 (2016): 397. http://dx.doi.org/10.3319/tao.2015.11.27.01(tem).

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Bora, Dipok K., Vladimir yu Sokolov, and Friedemann Wenzel. "Validation of strong-motion stochastic model using observed ground motion records in north-east India." Geomatics, Natural Hazards and Risk 7, no. 2 (September 26, 2014): 565–85. http://dx.doi.org/10.1080/19475705.2014.960011.

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Lin, Jeng Hsiang. "Time Series Modeling of Earthquake Ground Motions Using ARMA-GARCH Models." Applied Mechanics and Materials 470 (December 2013): 240–43. http://dx.doi.org/10.4028/www.scientific.net/amm.470.240.

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Engineers are well aware that, due to the stochastic nature of earthquake ground motion, the information obtained from structural response analysis using scant records is quite unreliable. Thus, providing earthquake models for specific sites or areas of research and practical implementation is essential. This paper presents a procedure for the modeling strong earthquake ground motion based on autoregressive moving average (ARMA) models. The Generalized autoregressive conditional heteroskedasticity (GARCH) model is used to simulate the time-varying characteristics of earthquakes.

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Guatteri, M. "Strong Ground-Motion Prediction from Stochastic-Dynamic Source Models." Bulletin of the Seismological Society of America 93, no. 1 (February 1, 2003): 301–13. http://dx.doi.org/10.1785/0120020006.

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Vlachos, Christos, Konstantinos G. Papakonstantinou, and George Deodatis. "Structural Applications of a Predictive Stochastic Ground Motion Model: Assessment and Use." ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 4, no. 2 (June 2018): 04018006. http://dx.doi.org/10.1061/ajrua6.0000946.

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Laouami, Nasser, Pierre Labbé, and Ramdane Bahar. "Stochastic model of seismic torsional ground motion: Application to Lotung soft site." Journal of Seismology 9, no. 4 (October 2005): 463–72. http://dx.doi.org/10.1007/s10950-005-2842-7.

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Pischiutta, Marta, Aybige Akinci, Elisa Tinti, and André Herrero. "Broad-band ground-motion simulation of 2016 Amatrice earthquake, Central Italy." Geophysical Journal International 224, no. 3 (August 31, 2020): 1753–79. http://dx.doi.org/10.1093/gji/ggaa412.

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SUMMARY On 24 August 2016 at 01:36 UTC a ML6.0 earthquake struck several villages in central Italy, among which Accumoli, Amatrice and Arquata del Tronto. The earthquake was recorded by about 350 seismic stations, causing 299 fatalities and damage with macroseismic intensities up to 11. The maximum acceleration was observed at Amatrice station (AMT) reaching 916 cm s–2 on E–W component, with epicentral distance of 15 km and Joyner and Boore distance to the fault surface (RJB) of less than a kilometre. Motivated by the high levels of observed ground motion and damage, we generate broad-band seismograms for engineering purposes by adopting a hybrid method. To infer the low frequency seismograms, we considered the kinematic slip model by Tinti et al . The high frequency seismograms were produced using a stochastic finite-fault model approach based on dynamic corner-frequency. Broad-band synthetic time-series were therefore obtained by merging the low and high frequency seismograms. Simulated hybrid ground motions were compared both with the observed ground motions and the ground-motion prediction equations (GMPEs), to explore their performance and to retrieve the region-specific parameters endorsed for the simulations. In the near-fault area we observed that hybrid simulations have a higher capability to detect near source effects and to reproduce the source complexity than the use of GMPEs. Indeed, the general good consistency found between synthetic and observed ground motion (both in the time and frequency domain), suggests that the use of regional-specific source scaling and attenuation parameters together with the source complexity in hybrid simulations improves ground motion estimations. To include the site effect in stochastic simulations at selected stations, we tested the use of amplification curves derived from HVRSs (horizontal-to-vertical response spectra) and from HVSRs (horizontal-to-vertical spectral ratios) rather than the use of generic curves according to NTC18 Italian seismic design code. We generally found a further reduction of residuals between observed and simulated both in terms of time histories and spectra.

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Wen, Y. K., and C. L. Wu. "Uniform Hazard Ground Motions for Mid-America Cities." Earthquake Spectra 17, no. 2 (May 2001): 359–84. http://dx.doi.org/10.1193/1.1586179.

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For performance evaluation of buildings and structures, synthetic uniform hazard (10% and 2% in 50 years) ground motions are generated for Memphis, Tennessee, St. Louis, Missouri, and Carbondale, Illinois. The method of simulation is based on the latest regional seismic information and stochastic ground motion models. Both point-source model and finite-fault model are used and the effects of soil profile are considered. The emphasis is on treatment of uncertainty and efficiency in application to evaluation of structural performance in both the linear and nonlinear range. The results show that the uniform hazard response spectra calculated from the simulated motions are comparable to those corresponding to USGS hazard maps. The suites of ten ground motions selected to match the uniform hazard response spectra represent events of different magnitudes, distances, and attenuation. The median value of the structural response to the selected ground motions matches closely the uniform hazard linear and nonlinear response spectra based on nine thousand ground motions and has a coefficient of variation of less than 10%. The suites of uniform hazard ground motions therefore can be used in probabilistic performance evaluation with good accuracy and efficiency.

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Beresnev, Igor A., and Gail M. Atkinson. "Stochastic finite-fault modeling of ground motions from the 1994 Northridge, California, earthquake. I. Validation on rock sites." Bulletin of the Seismological Society of America 88, no. 6 (December 1, 1998): 1392–401. http://dx.doi.org/10.1785/bssa0880061392.

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Abstract The stochastic method of simulating ground motions from finite faults is validated against strong-motion data from the M 6.7 1994 Northridge, California, earthquake. The finite-fault plane is subdivided into elements, each element is assigned a stochastic ω2 spectrum, and the delayed contributions from all subfaults are summed in the time domain. Simulated horizontal acceleration time histories and Fourier spectra at 28 rock sites are compared with observations. We first perform simulations using the slip distribution on the causative fault derived from strong-motion, teleseismic, GPS, and leveling data (Wald et al., 1996). We then test the performance of the method using quasi-random distributions of slip and alternative hypocenter locations; this is important because the rupture initiation point and slip distribution are in general not known for future earthquakes. The model bias is calculated as the ratio of the simulated to the observed spectrum in the frequency band of 0.1 to 12.5 Hz, averaged over a suite of rock sites. The mean bias is within the 95% confidence limits of unity, showing that the model provides an accurate prediction of the spectral content of ground motions on average. The maximum excursion of the model bias from the unity value, when averaged over all 28 rock stations, is a factor of approximately 1.6; at most frequencies, it is below a factor of 1.4. Interestingly, the spectral bias and the standard deviation of the stochastic simulations do not depend on whether the fault slip distribution and hypocenter location are based on data or are randomly generated. This suggests that these parameters do not affect the accuracy of predicting the average characteristics of ground motion, or they may have their predominant effect in the frequency range below about 0.1 Hz (below the range of this study). The implication is that deterministic slip models are not necessary to produce reasonably accurate simulations of the spectral content of strong ground motions. This is fortunate, because such models are not available for forecasting motions from future earthquakes. However, the directivity effects controlled by the hypocenter location are important in determining peak ground acceleration at individual sites. Although the method is unbiased when averaged over all rock sites, the simulations at individual sites can have significant errors (generally a factor of 2 to 3), which are also frequency dependent. Factors such as local geology, site topography, or basin-propagation effects can profoundly affect the recordings at individual stations. To generate more accurate site-specific predictions, empirical responses at each site could be established.

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Noori, M. S. M., and R. M. Abbas. "Reliability Analysis of an Uncertain Single Degree of Freedom System Under Random Excitation." Engineering, Technology & Applied Science Research 12, no. 5 (October 2, 2022): 9252–57. http://dx.doi.org/10.48084/etasr.5193.

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In practical engineering problems, uncertainty exists not only in external excitations but also in structural parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of portal frames subjected to random ground motions. The North-South component of the El Centro earthquake in 1940 in California is selected as the ground excitation. Using the power spectral density function, the two-dimensional finite element model of the portal frame’s base motion is modified to account for random ground motions. A probabilistic study of the portal frame structure using stochastic finite elements utilizing Monte Carlo simulation is presented using the finite element program ABAQUS. The dynamic reliability and probability of failure of stochastic and deterministic structures based on the first-passage failure were examined and evaluated. The results revealed that the probability of failure increases due to the randomness of stiffness and mass of the structure. The influence of uncertain parameters on reliability analysis depends on the extent of variance in structural parameters.

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Tchawe, F. N., C. Gelis, L. F. BONILLA, and F. Lopez-Caballero. "Effects of 2-D random velocity perturbations on 2-D SH short-period ground motion simulations in the basin of Nice, France." Geophysical Journal International 226, no. 2 (April 12, 2021): 847–61. http://dx.doi.org/10.1093/gji/ggab141.

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SUMMARY Some geological configurations, like sedimentary basins, are prone to site effects. Basins are often composed of different geological layers whose properties are generally considered as spatially homogeneous or smoothly varying. In this study, we address the influence of small-scale velocity fluctuations on seismic response. For this purpose, we use the spectral element method to model the 2-D SH wave propagation on a basin of 1.1 km long and ≈ 60 m deep, representing a 2-D profile in the city of Nice, France. The velocity fluctuations are modelled statistically as a random process characterized by a Von Karman autocorrelation function and are superimposed to the deterministic model. We assess the influence of the amplitude and correlation length of the random velocities on the surface ground motion. We vary the autocorrelation function’s parameters and compute seismic wavefields in 10 random realizations of the stochastic models. The analyses of our results focus on the envelope and phase differences between the waveforms computed in the random and deterministic models; on the variability of ground motion intensity measures, such as the peak ground velocity, the pseudo-spectral acceleration response; and the 2-D basin response (transfer function). We find that the amplitude of fluctuations has a greater effect on the ground motion variability than the correlation length. Depending on the random medium realization, the ground motion in one stochastic model can be locally amplified or deamplified with respect to the reference model due to the presence of high or low velocity contrasts, respectively. When computing the mean amplification of different random realizations, the results may be smaller than those of the reference media due to the smoothing effect of the average. This study highlights the importance of knowing the site properties at different scales, particularly at small scales, for proper seismic hazard assessment.

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Sokolov, Vladimir Yu. "Spectral parameters of the ground motions in Caucasian seismogenic zones." Bulletin of the Seismological Society of America 88, no. 6 (December 1, 1998): 1438–44. http://dx.doi.org/10.1785/bssa0880061438.

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Abstract A collection of ground-motion recordings including accelerograms of the mainshock of the 7 December 1988, Spitak earthquake (M = 6.9, Northern Armenia) has been obtained during the 1988 to 1990 strong-ground-motion network operation. This region of the Caucasus still has a poor database for strong-ground-motion prediction, but the data studied here form a basis for source scaling and attenuation relation study. The results show that the acceleration spectra of shear waves recorded at rock sites can be modeled accurately by the Brune source model using a stress parameter of 50 to 100 bar (Spitak area) and 200 bar (events to the North from the Spitak area), and cutoff frequency fmax = 7 to 10 Hz. The anelastic attenuation Q of spectral amplitudes with distance may be described by the form published by Boore (1987) Q = 29.4 [1 + (f/0.3)2.9]/(f/0.3)2 up to distances R = 70 km. The comparison of modeled bedrock spectra with observed data (registered at shallow soil deposits) allowed the author to estimate the local site response in terms of frequency-dependent amplification functions. The generalized regional amplification function was used to predict ground motion in conditions of shallow soils. Stochastic simulation of ground motions (peak ground acceleration and response spectra) using the obtained models of source spectra and attenuation shows good agreement with observed data.

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Liao, S., and J. Li. "A stochastic approach to site-response component in seismic ground motion coherency model." Soil Dynamics and Earthquake Engineering 22, no. 9-12 (October 2002): 813–20. http://dx.doi.org/10.1016/s0267-7261(02)00103-3.

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Journal articles on the topic 'Stochastic ground motion model'

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