Variability Of Ground Motion Research Articles

Nonlinear Analysis of Bridges Considering Soil–Structure Interaction and Travelling Wave Effects Under Combined Train and Near-Fault Seismic Loads

This paper presents a comprehensive method for analyzing prestressed concrete bridges subjected to multiple concurrent dynamic loads, incorporating soil–structure interaction (SSI) and seismic wave propagation effects. The study develops a comprehensive numerical framework that simultaneously accounts for traveling seismic waves, train-induced vibrations, and soil–foundation dynamics. Three-dimensional finite element modeling captures the complex interaction between the bridge structure, foundation system, and surrounding soil medium. The investigation considers the spatial variability of ground motion and its influence on the bridge’s dynamic response, particularly examining how different wave velocities and coherency patterns affect structural behavior. Advanced material constitutive models based on damage mechanics theory are implemented to represent both linear and non-linear structure responses under dynamic loading conditions. The analysis reveals that traditional simplified approaches, which neglect SSI, train, and seismic loading combinations, and traveling wave effects may significantly misestimate the structural demands. The results demonstrate how wave passage effects can either amplify or attenuate the combined response depending on the relationship between seismic wave velocity, the frequency content of the ground motion recordings, and the local soil conditions. These findings could contribute to the development of more reliable design methodologies for prestressed bridges in seismically active regions with significant railway traffic.

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Impact of $${{\varvec{M}}}_{{\varvec{W}}}$$ definition approach on Fourier ground-motion variability of shallow crustal earthquakes in Europe

Impact of $${{\varvec{M}}}_{{\varvec{W}}}$$ definition approach on Fourier ground-motion variability of shallow crustal earthquakes in Europe

A study of the nonlinear behaviour of the irregular Beni Haroun cable-stayed bridge to progressive seismic failure under SVGM

The progressive failure of the nonlinear irregular Cable-Stayed Bridges (CSBs) under Spatial Variability of Ground Motions (SVGM) counting seismic wave propagation, incoherence effect and site-response effect is investigated. A spectral representation method is used in order to develop a computer code. This code is used to simulate SVGM time histories to be compatible with an overall coherency function and a target response spectrum, A three-dimensional Finite Element Model (FEM) of an asymmetric bridge: the Beni Haroun cable-stayed bridge (CSB) (North Eastern Algeria) is developed in order to include the effects of the main components of SVGM on response parameters in terms of variations of absolute maximum vertical displacements and flexural moments along the deck and on height of short and tall pylons of study CSB, in particular, nonlinear bridge response quantities are examined in terms of rotational ductility demands at the ends of the short and tall piers of the bridge under all components of SVGM. The numerical results are comforted with those obtained assuming uniform seismic excitations. The analysis results reveal, among others, that the bridge responses are very sensitive to the SVGM, with site-response effects being more critical for bridge response than those of incoherence components and wave propagation. As a general trend, it is showed that the assumption of uniform excitation results in much lower ductility demands on bridges than incoherence and site SVGM components and that the latter should be considered for the seismic response assessments and progressive seismic failure studies of irregular cable-stayed bridges.

Advantages of base isolation in reducing the reliability sensitivity to structural uncertainties of buildings

Base isolation is among the most effective techniques for safeguarding buildings against earthquakes. Similar to non-isolated buildings, the seismic performance of a base-isolated building can vary not only due to the inherent record-to-record variability in earthquake ground motions but also the non-negligible influence of uncertainties associated with structural properties. Introducing an isolation layer of isolation bearings and energy dissipators to the building further adds to the source of uncertainties, raising the question regarding the reliability of base isolated buildings. This study proposed a methodology that employs the probability density evolution method (PDEM) with local time grid refinement to evaluate the reliability of a base-isolated structure and its non-isolated counterpart under earthquakes of various magnitudes and fault distances. It allows for simultaneously considering the uncertainties of various sources in the reliability analyses with affordable computational cost, including those of the ground motions, of the structural nonlinearity, and of the ultimate states that define the reliability. The results show that the base-isolated building exhibits much higher reliability than its non-isolated counterpart in all cases even if the ultimate behavior such as the isolator fracture or the impact to the retaining wall is considered. The added source of uncertainties in the isolation layer does not exhibit a notable impact on the reliability. In contrast, the seismic reliability of base-isolated buildings is much less sensitive to structural uncertainties than that of their non-isolated counterparts.

Comparative Study of Semi-Active Control Effectiveness of Structures on Soft Soil Using MR Damper: Shaking Table Investigation

The effect of soil-structure interaction (SSI) cannot be neglected in semi-active vibration control of structures located on soft soil. To investigate the mitigating effect of magnetorheological (MR) damper on the semi-active control of structures considering the SSI, shaking table tests were conducted to evaluate the performance of the MR damper-based semi-active control system for structures on soft soil. In addition to a novel fuzzy control method based on online learning deep neural network (OL-DFNN), various control strategies, including passive OFF, passive ON, ON–OFF and deep neural network fuzzy control (DFNN) were systematically evaluated. The test results showed that the OL-DFNN control method exhibited superior adaptability to varying ground motion and structural dynamic characteristics compared to the other control methods. In particular, the OL-DFNN controller effectively mitigated the peak displacement and root mean square displacement, outperforming the passive OFF, passive ON, ON–OFF and DFNN control strategies. The test results highlight the effectiveness of the OL-DFNN control method in addressing the challenges posed by dynamic and time-varying characteristics in structural vibration control systems considering SSI.

Dynamic reliability assessment for high CFRDs incorporating ground motion and material parameter variability via GPDEM

The randomness of earthquake and material parameters significantly impacts the seismic response and dynamic reliability of geotechnical engineering structures. In this study, a dynamic reliability analysis method for high concrete face rockfill dams (CFRDs) under the influence of random factors is proposed by combining random sample generation methods with the generalized probability density evolution method (GPDEM). Firstly, the spectral representation-random function method is employed to achieve dimensionality reduction expression for intensity-frequency non-stationary ground motion. Sensitivity analysis is then used to identify the random variables of the rockfill constitutive model, and the improved generalized F-discrepancy (GF-discrepancy) method is utilized to generate random material parameters. Then, the random samples of earthquake and material parameter are introduced into the finite element calculation of CFRD, conducting a series of dynamic finite element calculations. Finally, GPDEM is used to derive probability information and dynamic reliability from the deterministic time history responses. The results indicate that random factors contribute to the variability of seismic response and dynamic reliability. Stochastic ground motion significantly affects extreme values, while variability in material parameters has a more pronounced influence on the overall process of seismic response. These findings provide valuable references for the seismic design of CFRDs.

A Resolution of the Variability Discrepancy Between Peak Ground Acceleration and Spectral Stress Drop

Abstract It has been recognized that the between-event variability of peak ground acceleration (PGA) is significantly smaller than the variability of the stress drop calculated from corner frequency (the spectral stress drop). Resolving this discrepancy is indispensable for improving seismic hazard assessment because the spectral stress drop is considered a fundamental parameter for predicting high-frequency ground motions. This study addresses this paradox for Mw 3.6–7.1 crustal earthquakes in Japan. Two factors are essential for resolving the problem: (1) calculating the spectral stress drop using a high-frequency-fitted corner frequency (called the stress parameter Δσfch) and (2) considering the magnitude dependence of Δσfch. To estimate Δσfch, the source spectra for crustal earthquakes in Japan are obtained using the two-stage spectral ratio method, which enables the estimation of double-corner-frequency spectra. This two-stage approach is more effective for accurately estimating Δσfch than the standard spectral ratio approach that assumes the single-corner frequency model. This study shows that Δσfch increases with increasing magnitude up to Mw∼5.5 and then becomes constant. The variability of Δσfch calculated by considering this magnitude dependence of Δσfch aligns with the between-event variability of PGA. Incorporating a double-corner-frequency model is crucial for predicting ground-motion variability and enhancing seismic hazard assessments.

Seismic Performance of Pile Groups under Liquefaction-Induced Lateral Spreading: Insights from Advanced Numerical Modeling

Post-earthquake investigations have shown that piles in liquefiable soils are highly susceptible to damage, especially in sloping sites. This study examines the seismic performance of pile groups with lateral spreading through advanced numerical modeling. A three-dimensional finite element model, validated against large-scale shaking table test results, is implemented to capture the key mechanisms driving the dynamic response of pile groups under both inertial and kinematic loading conditions. Parametric seismic response analyses are conducted to compare the behavior of batter and vertical piles under varying ground motion intensities. The results indicate that batter piles experience increased axial compressive and tensile forces compared to vertical piles, up to 70% and 20%, respectively. However, batter piles provide enhanced lateral stiffness and shear resistance compared to vertical piles, reducing horizontal displacements by up to 20% and tilting the cap by 85% under strong ground motion. The results demonstrate that batter piles not only enhance the overall seismic stability of the structure but also mitigate the risk of liquefaction-induced lateral spreading in the near-field through pile-pinning effects. While vertical piles are more commonly used in practice, the distinct advantages of batter piles for seismic stability highlighted in this study may encourage using more advanced numerical modeling in engineering projects.

Broadband Ground-Motion Simulations with Machine-Learning-Based High-Frequency Waves from Fourier Neural Operators

ABSTRACT Seismic hazards analysis relies on accurate estimation of expected ground motions for potential future earthquakes. However, obtaining realistic and robust ground-motion estimates for specific combinations of earthquake magnitudes, source-to-site distances, and site conditions is still challenging due to the limited empirical data. Seismic hazard analysis also benefits from the simulation of ground-motion time histories, whereby physics-based simulations provide reliable time histories but are restricted to a lower frequency for computational reasons and missing information on small-scale earthquake-source and Earth-structure properties that govern high-frequency (HF) seismic waves. In this study, we use densely recorded acceleration broadband (BB) waveforms to develop a machine-learning (ML) model for estimating HF ground-motion time histories from their low-frequency (LF) counterparts based on Fourier Neural Operators (FNOs) and Generative Adversarial Networks (GANs). Our approach involves two separate FNO models to estimate the time and frequency properties of ground motions. In the time domain, we establish a relationship between normalized low-pass filtered and BB waveforms, whereas in the frequency domain, the HF spectrum is trained based on the LF spectrum. These are then combined to generate BB ground motions. We also consider seismological and site-specific factors during the training process to enhance the accuracy of the predictions. We train and validate our models using ground-motion data recorded over a 20 yr period at 18 stations in the Ibaraki province, Japan, considering earthquakes in the magnitude range M 4–7. Based on goodness-of-fit measures, we demonstrate that our simulated time series closely matches recorded observations. To address the ground-motion variability, we employ a conditioned GAN approach. Finally, we compare our results with several alternative approaches for ground-motion simulation (stochastic, hybrid, and ML-based) to highlight the advantages and improvements of our method.

Synthetic ground motions in heterogeneous geologies from various sources: the HEMEWS-3D database

Abstract. The ever-improving performances of physics-based simulations and the rapid developments of deep learning are offering new perspectives to study earthquake-induced ground motion. Due to the large amount of data required to train deep neural networks, applications have so far been limited to recorded data or two-dimensional (2D) simulations. To bridge the gap between deep learning and high-fidelity numerical simulations, this work introduces a new database of physics-based earthquake simulations. The HEterogeneous Materials and Elastic Waves with Source variability in 3D (HEMEWS-3D) database comprises 30 000 simulations of elastic wave propagation in 3D geological domains. Each domain is parametrized by a different geological model built from a random arrangement of layers augmented by random fields that represent heterogeneities. Elastic waves originate from a randomly located pointwise source parametrized by a random moment tensor. For each simulation, ground motion is synthesized at the surface by a grid of virtual sensors. The high frequency of waveforms (fmax⁡=5 Hz) allows for extensive analyses of surface ground motion. Existing and foreseen applications range from statistical analyses of the ground motion variability and machine learning methods on geological models to deep-learning-based predictions of ground motion that depend on 3D heterogeneous geologies and source properties. Data are available at https://doi.org/10.57745/LAI6YU (Lehmann, 2023).

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity (VS) structure, which is the main ingredient for estimating the variability of site response. As such, VS can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus VS can substantially modify ground shaking during earthquakes. We apply a novel VS randomization approach to propagate the small-scale heterogeneities of VS to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of VS profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of VS small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

High‐Resolution Seismicity and Ground Motion Variability Across the Highly Locked Southern Anninghe Fault With Dense Seismic Arrays and Machine Learning Techniques

AbstractFault activity and structure are important factors for the assessment of seismic hazards. The Anninghe fault is one of the most active strike‐slip faults in southwestern China but has been experiencing seismic quiescence for M > 4 earthquakes since the 1970s. To understand better the characteristics of its highly locked southern segment, we investigate seismicity and ground motion variability using recently deployed multi‐scale dense arrays. Assisted by machine learning (ML) seismic phase picking and event discrimination models, we first compile a high‐resolution catalog of local seismic events. We find limited earthquakes that occurred on the Anninghe fault, consistent with its generally acknowledged high locking degree. Whereas, most newly detected events appear within off‐fault clusters, among which four are closely related to anthropogenic activities (e.g., mining blasts), and two neighboring faults host the remaining ones. We further apply an ML‐based first‐motion polarity (FMP) classifier and successfully obtain a reliable small earthquake focal mechanism, which agrees well with the geologically inferred north‐south trending and eastward dipping of the Anninghe fault. Analyses of ground motion variations along two across‐fault linear arrays show abrupt changes in FMPs and obvious frequency‐dependent site amplifications near the mapped fault traces. It further suggests that, at finer scales, the damaged Anninghe fault zone may have split into two smaller damaged zones at shallower depths, resulting in a typical “flower‐type” fault structure. The efficient workflow developed in this study can be well applied for the longer‐term monitoring and better characterization of the southern Anninghe fault, or other similar regions.

Assessment of the seismic failure of reinforced concrete structures considering the directional effects of ground motions

Seismic intensity measures at different levels significantly impact the seismic damage of building clusters. Reinforced concrete (RC) structures are a type of building widely used in different regions worldwide. A large amount of field seismic damage observation data indicates that within the same seismic intensity zone, the directional effects of varying ground motions lead to significant differences in damage to RC structures on different floors. However, relatively little research has been conducted on estimating the seismic fragility and vulnerability of RC structures considering the directional effects of seismic action. To further study the directional effect of seismic motion on the damage of different floors, this study conducted dynamic time history and spectral analyses on 1472,379 acceleration records in multiple directions obtained from monitoring at nine actual seismic stations during the 2008 Wenchuan earthquake in China. This paper innovatively reports on the actual damage features of RC structures during the Mw6.2 magnitude Jishishan earthquake in Gansu Province, China, on December 18, 2023 (the most severe destructive earthquake in China in 2023) and analyses the influence of earthquake directionality on the damage to different floors of RC structures. A three-dimensional numerical model of a four-story RC frame structure was established using numerical simulation and the finite element method. Different intensity measures were taken to input seismic excitations of different intensities into the RC structure in the 0°, 30°, 60°, and 90° directions, and damage simulation analysis was conducted. The nonlinear dynamic time history curves of structures under multiple directions of seismic excitation in different intensity zones have been developed. Using the interstory stiffness and interstory displacement angle as engineering demand parameters, damage assessment curves and stress clouds for RC structures with 1–4 floors considering different seismic directional effects were generated. The analysis results and major findings indicate that the seismic sequence in the 0° direction has a relatively heavy impact on the first floor of the RC structure in zone IX, which is consistent with the actual field observation results.

Probabilistic damage evaluation of isolated steel box-girder bridge excited by near-field earthquakes

Modern civilization regards bridges as lifelines, and their failure due to significant earthquakes in the past has raised concerns about their seismic vulnerability. The effect of near-fault earthquakes on the bridge vulnerability is a significant problem that has not been well explored. The present work utilizes fragility analysis to assess the probabilistic seismic risk evaluation of a continuous isolated steel box girder bridge exposed to near-field ground motions (NFGMs). Probabilistic seismic demand models (PSDMs) of the bridge are explored to reliably associate key demand and intensity measures to capture the seismic performance of the system. This study examines a steel box girder bridge in Guwahati, India, isolated with lead rubber (LRB) bearings and a friction pendulum system (FPS). To achieve a comparable seismic response, each bearing system is designed for a similar isolation period. The PGV/PGA ratio is a useful metric for classifying ground motion suites and estimating their frequency content by classifying the input excitations into low- and high-frequency motions. To perform probabilistic seismic risk assessments, two ensembles of forward directivity records with PGV: PGA >160 cm/s/g (high frequency) and PGV: PGA <160 cm/s/g (low frequency) are considered. Moreover, one ensembles of near-field incorporating the fling effect and far-field are also utilized. The failure probability under the seismic hazards for isolated bridges is assessed utilizing different damage measures (DM) such as maximum displacement ductility of pier (DDP), displacement of deck (MDD), drift ratio of pier (PDR), and rotational ductility (RDP). The near-field earthquake damage probability is significantly impacted by the PGV/PGA ratio, as a high PGV/PGA ratio results in a greater probability of damage than a low PGV/PGA ratio. In conclusion, guidelines are provided that will help the design engineers for designing bridges with LRB and FPS isolators for seismic isolation in the event of varying ground motion characteristics.

Assessing seismic hazard and uncertainty in Büyükçekmece using ground motion simulations

This study presents a comprehensive seismic hazard assessment for Büyükçekmece, a district in Istanbul, Turkey, situated near the seismically active North Anatolian Fault (NAF). The study utilizes stochastic ground motion simulations with the validated EXSIM algorithm to understand the potential impact of medium to large-magnitude earthquakes (ranging from MW 6.3 to 7.42) on this vulnerable community. The research employs a site-specific approach, considering unique amplification factors for each location. By conducting 50 scenario-based simulations, the study assesses the seismic hazard, highlighting the importance of comprehending variations in ground motion, even when they are small, for a more precise hazard assessment. Furthermore, this study addresses the critical issue of uncertainty, particularly concerning stress parameters and hypocenter locations. The researchers demonstrate that variability in these factors can introduce substantial uncertainty in ground motion predictions. The study provides insights into the range of potential ground motion outcomes through probabilistic assessments involving multiple scenarios and stress drop values. Notably, the results indicate that ground motion levels vary with earthquake magnitudes and underscore the significance of accounting for this variability. This research emphasizes the seismic vulnerability of Büyükçekmece and the importance of accurate ground motion simulations, offering valuable insights for earthquake preparedness and mitigation efforts in the region.

Seismic fragility assessment of an in-service piled bridge abutment subjected to a liquefaction-induced lateral spreading and mitigation strategy

This study assesses the seismic fragility curves of in-service piled bridge abutments on liquefaction-prone soils and evaluates an optimal countermeasure within the vulnerability framework. Seismic fragility curves, accounting for varying ground motion intensities, assess the seismic risk and describe abutment damage through settlement measurements. The ageing abutment performance is estimated by integrating a corrosion model into fragility curves. The impact of different sheet pile positions on the seismic performance of in-service piled bridge abutments is analysed, and the optimal pile position is discussed. The developed fragility curves provide a rapid and effective risk assessment tool for the seismic performance of in-service abutments and guide liquefaction remedial measures.

Influence of ground motion variables on the nonlinear seismic demand of masonry-infilled reinforced concrete frames

Influence of ground motion variables on the nonlinear seismic demand of masonry-infilled reinforced concrete frames

Ground motion prediction using Artificial Neural Network in Pakistan

The goal of this research project is to design, build, and validate an artificial neural network (ANN) model that predicts ground motion from the previous data of earthquake for seismic incidents in Pakistan. The prediction of ground motion is essential for determining the seismic risks and consequently providing measures to mitigate them. The ANN model implements activation function in hidden neurons to represent those relationships the seismic data holds and get logarithmic PGA values. The model performance evaluation metrics which are like Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Correlation Coefficients prove the accuracy and robustness of the ANNPGA model. The ANNPGA model displays the best predictive power of all PGA values through the validation dataset. The MSE value is 0.00264 which model's accuracy in capturing ground motion variability. A comparative analysis with already created empirical and physics-based models will demonstrate that the ANPGA model gives more accurate predictions in most cases and especially in situations where nonlinear relationships are involved.

Nonstationary elastoplastic response analysis of curved beam bridges under spatial variability of earthquake ground motion using absolute displacement method

Current studies indicate that curved beam bridges are more sensitive to the spatial variability of earthquake ground motion (SVEGM) than straight bridges. However, research methods used currently typically disregard the nonlinear characteristics of bridges or use only deterministic excitations for analysis. Furthermore, the sensitivity of curved beam bridges with different curvature radii to the SVEGM has not been investigated comprehensively. Hence, in this study, a nonlinear finite element model of curved beam bridges is established using the ANSYS platform and the MATLAB is then employed to reduce and decouple the non-stationary seismic evolutionary power spectral density (EPSD) matrix. The absolute displacement method is employed for the multidimensional and multipoint nonlinear time-history analysis of the bridges. Considering different wave velocities, site conditions, and coherence types, this study comprehensively analyses the random response and frequency domain characteristics of curved continuous beam bridges under different SVEGMs. The analysis includes a verification of curved beam bridges with different curvature radii based on 48 cases (six SVEGMs with eight curvature radii). The results indicate that the presence of curvature renders curved beam bridges more sensitive to the SVEGM. The SVEGM significantly affects the random response and response frequency domain distribution of curved beam bridges, with smaller curvature radii contributing more significantly to the response. Therefore, the SVEGM must be considered in the seismic analysis of curved beam bridges, particularly those with smaller radii, to avoid an inaccurate estimation of the seismic performance of the bridges. The findings of this study can improve the seismic design and evaluation of curved beam bridges as well as enhance their seismic performance and reliability.