Ground Shaking Intensity Research Articles

Near-Real-Time Strong Motion Acquisition at National Scale and Automatic Analysis.

A strong motion monitoring network records data that provide an excellent way to study how source, path, and site effects influence the ground motion, specifically in the near-source area. Such data are essential for updating seismic hazard maps and consequently building codes and earthquake-resistant design. This paper aims to present the Italian Strong Motion Network (RAN), describing its current status, employment, and further developments. It has 648 stations and is the result of a fruitful co-operation between the Italian government, regions, and local authorities. In fact, the network can be divided into three sub-networks: the Friuli Venezia Giulia Accelerometric Network, the Irpinia Seismic Network, and all the other stations. The Antelope software automatically collects, processes, and archives data in the data acquisition centre in Rome (Italy). The efficiency of the network on a daily basis is today more than 97%. The automatic and fast procedures that run in Antelope for the real-time strong motion data analysis are continuously improved at the University of Trieste: a large set of strong motion parameters and correspondent Ground Motion Prediction Equations allow ground shaking intensity maps to be provided for moderate to strong earthquakes occurring within the Italian territory. These maps and strong motion parameters are included in automatic reports generated for civil protection purposes.

Medium-run local economic effects of a major earthquake

AbstractExisting research is inconclusive regarding the longer-term economic effects of earthquakes. We examine the medium-run impacts of the 2010 earthquake in Chile, the sixth-largest ever recorded, using value-added tax collection as a proxy for economic activity at the municipal level and a measure of local ground-shaking intensity. We find that the affected municipalities suffered a relevant and persistent drop in their economic activity of about 10%, 8–9 years after the event. We discuss the plausibility of the assumption of conditional parallel trends and show that the overall results are robust to using alternative estimation methods.

Correlation of Performance of Reinforced Concrete Buildings with Energy-Based Parameters

Background: The intensity of ground shaking and the demand on structures during earthquakes have been generally characterized using parameters such as peak ground acceleration as well as strength-based parameters such as response spectrum ordinates (e.g., spectral acceleration), which represent the maximum amplitude of shaking for structures with specified natural period and damping values. Methods: It has long been recognized that to assess the demands on structures during earthquakes, one might employ an energy-based approach (as an alternative to the more common strength-based one), especially when there is an interest in assessing the damage potential of ground motions. The study focuses on the correlation between Ground Motion Parameters (GMPs) and structural damage indicators for reinforced concrete frames. The relationship between ground motion intensity and structural damage is of primary concern in seismic regions. Here, we consider GMPs that are strength-based (such as spectral acceleration, Sa) and energy-based (such as input energy-equivalent acceleration, Ai, and absorbed energy-equivalent acceleration, Aa), as defined in the study. In order to evaluate Ground Motion Parameters (GMPs) for efficiency, power-law format regression studies of damage measures (DM) on each GMP are utilized. Results: The general objective of this paper is to investigate if energy-based parameters can correlate well with structural damage. Thus, power-law formats in regression of damage on GMP are considered. In regression studies of this type, a lower standard deviation of the damage measure given the value of the ground motion parameter (GMP) is considered an indication of a stronger correlation between that damage measure and the corresponding ground motion parameter. Conclusion: These extensive regression studies are carried out for both low-rise and high-rise reinforced concrete buildings. Conclusions are discussed following these analyses.

Line‐Source Model Based Rapid Inversion for Deriving Large Earthquake Rupture Characteristics Using High‐Rate GNSS Observations

AbstractWe present a new method using Global Navigation Satellite System‐derived peak ground velocities to rapidly determine rupture characteristics for large earthquakes (Mw > 6). A three‐step strategy is adopted to sequentially estimate the fault rupture length, direction, and pattern (unilateral or bilateral). It does not require any a priori constraint on the fault plane, and can avoid drift and clipping problems in seismic data based inversion methods. Through retrospective analysis of six recent large earthquakes, the line‐source rupture characteristics can be determined within 30 s. Comparison with the United States Geological Survey released products demonstrates that the line‐source parameters can be estimated with considerable accuracy. We also analyze the contribution of the earthquake rupture characteristics to the prediction of ground shaking intensity. It is shown that the method has the potential to improve ground shaking predictions with applications in disaster assessment and emergency response.

An Appraisal of Ground Failure and Hydrogeological Changes Associated with the 28 April 2021 Mw 6 Sonitpur Earthquake, Assam, India, Using Field Evidences and InSAR Measurements

Abstract Widespread damage and coseismic ground disturbances are generally associated with large magnitude and/or shallow focus earthquakes. Surprisingly, a deep focus (34 km), moderate magnitude earthquake (Mw 6) occurred near the Kopili fault zone in Sonitpur district, Assam, India, on 28 April 2021 and created intense ground shaking and extensive damage along the Brahmaputra Valley. We undertook a field survey within a day after the earthquake and carried out Interferometric Synthetic Aperture Radar (InSAR) analysis to map any coseismic ground deformation features. Our field survey revealed extensive liquefaction features and several coseismic secondary ground cracks along the alluvial tracts of the Brahmaputra River system. InSAR analysis revealed a sinistral slip up to ∼60 mm along a north-northwest–south-southeast-oriented previously unmapped lineament or fault. Field investigations revealed coseismic hydrological changes including a sudden rise and fall in the water level by 0.3–0.5 m followed by the injection of sand materials up to a thickness of 1.25 m in dug wells and the appearance of water in seasonally dried river channels and ponds. Interferometric coherence analysis during pre-, co-, and postseismic periods further confirmed the coseismic surge in water at five major tributary rivers of the Brahmaputra River. We speculate that the pressure difference at the shallow unconfined aquifer system of the mountain-front alluvial fan induced by coseismic stresses must have caused channeling of groundwater to the rivers and the contemporaneous water level fluctuations in wells. Amplification of seismic waves at the thick, unconsolidated sedimentary strata of the Brahmaputra Valley could have enhanced the extensive damage due to the 2021 Sonitpur earthquake. The present study has implications in estimating damage potential along the Brahmaputra Valley for future earthquakes.

Seismic vulnerability modelling of building portfolios using artificial neural networks

ABSTRACTThe incorporation of machine learning (ML) algorithms in earthquake engineering can improve existing methodologies and enable new frameworks to solve complex problems. In the present study, the use of artificial neural networks (ANNs) for the derivation of seismic vulnerability models for building portfolios is explored. Large sets of ground motion records (GMRs) and structural models representing the building stock in the Balkan region were used to train ANNs for the prediction of structural response, damage and economic loss conditioned on a vector of ground shaking intensity measures. The structural responses and loss ratios (LRs) generated using the neural networks were compared with results based on traditional regression models using scalar intensity measures in terms of efficiency, sufficiency, bias and variability. The results indicate a superior performance of the ANN models over traditional approaches, potentially allowing a greater reliability and accuracy in scenario and probabilistic seismic risk assessment.

Seismic vulnerability and resilience of steel-reinforced concrete (SRC) composite column buildings with non-seismic details

Prior to the enforcement of seismic details, older-type fully encased steel-reinforced concrete composite (SCR) columns were utilized in many buildings and bridges constructed in active seismic regions worldwide. However, there is serious lack of knowledge in the literature about the seismic behavior of older buildings’ SRC composite columns with non-seismic details. Shear strength expressions, stiffness, backbone curves, nonlinear modeling parameters, and acceptance criteria for these columns are not available. A recent testing campaign (led by the first author) provided more test data to characterize the cyclic performance of SRC columns with non-seismic details. The current study has three primary objectives (1) suggesting some test-based nonlinear modeling parameters for SRC columns; (2) developing fragility, vulnerability and resilience functions for an older-type building with non-seismic details SRC columns; and (3) assessing ASCE 41-17 SRC column modeling recommendations by comparing prototype building performance, fragility, vulnerability and resilience functions obtained using test-based backbone curves and proposed nonlinear modeling parameters with those obtained using ASCE 41-17 SRC column criteria. The methodology used to establish economic vulnerability functions accounts for uncertainties in ground motion, structural response, damages and losses by means of Monte Carlo simulation techniques. The vulnerability functions for the structural, non-structural and content components of the prototype building are established. The results of this study demonstrate that the ASCE 41-17 criteria significantly underestimates the structural capacity and resilience and overestimates the seismic fragility and vulnerability of the system; however, this may not be surprising considering the implicit conservatism included in structural engineering standards. The study shows that the ASCE 41-17 modeling criteria overestimates collapse probability by 30–50% for moderate ground shaking and by 5–15% for intense ground shaking.

Effects of Nonlinear Soil Behavior on Kappa (κ): Observations from the KiK-Net Database

ABSTRACTSoil nonlinear behavior is often triggered in soft sedimentary deposits subjected to strong ground shaking and has led to catastrophic damage to civil infrastructure in many past earthquakes. Nonlinear behavior in soils is associated with large shear strains, increased material damping ratio, and reduced stiffness. However, most investigations of the high-frequency spectral decay parameter κ, which captures attenuation, have focused on low-intensity ground motions inducing only small shear strains. Because studies of the applicability of the κ model when larger deformations are induced are limited, this article investigates the behavior of κ (both κr per record and site-specific κ0 estimates) beyond the linear-elastic regime. About 20 stations from the Kiban–Kyoshin network database, with time-average shear-wave velocities in the upper 30 m between 213 and 626 m/s, are used in this study. We find that the classification scheme used to identify ground motions that trigger soil nonlinear behavior biases estimates of κ0 in the linear and nonlinear regimes. A hybrid method to overcome such bias is proposed considering proxies for in situ deformation (via the shear-strain index) and ground shaking intensity (via peak ground acceleration). Our findings show that soil nonlinearity affects κr and κ0 estimates, but this influence is station dependent. Most κ0 at our sites had a 5%–20% increase at the onset of soil nonlinear behavior. Velocity gradients and impedance contrasts influence the degree of soil nonlinearity and its effects on κr and κ0. Moreover, we observe that other complexities in the wave propagation phenomenon (e.g., scattering and amplifications in the high-frequency range) impose challenges to the application of the κ0 model, including the estimation of negative values of κr.

Macro-Modelling Approach for the In-Plane Cyclic Response of Cold-Formed Steel Partition Walls

Past earthquakes demonstrate that non-structural elements could be vulnerable to a relatively low intensity ground shaking which induces negligible structural damage. The study aims to improve previously developed macro-models of cold-formed steel (CFS) partition walls to properly capture their in-plane cyclic response and damage states of important components in a CFS partition wall under imposed excitation. An effective analytical modelling approach is adopted for a simple modelling procedure and less computational effort. The proposed analysis model of partition walls consisting of several lumped spring elements is verified using direct comparison with two full scale CFS partition wall tests. The analytical and experimental results are compared in terms of force–displacement relations, dissipated energy, and an influential damage mechanism of components consisting of partition walls. The comparison shows that the analytical model well captures the experimental response such as the overall strength and stiffness degradation and pinching behavior. Moreover, the damage mechanism predicted by the analytical model is in good agreement with that observed during the tests.

Multi-Hazard Portfolio Loss Estimation for Time-Dependent Shaking and Tsunami Hazards

Megathrust subduction earthquakes generate intense ground shaking and massive tsunami waves, posing major threat to coastal communities. The occurrence of such devastating seismic events is uncertain and depends on their recurrence characteristics (e.g. inter-arrival time distribution and parameters) as well as elapsed time since the last major event. Current standard probabilistic loss models for earthquakes and tsunamis are based on a time-independent Poisson process and uniform earthquake slip distribution. Thereby, considerations of more realistic time-dependent earthquake occurrence and heterogeneous earthquake slip distribution are necessary. This study presents an innovative computational framework for conducting a time-dependent multi-hazard loss estimation of a building portfolio subjected to megathrust subduction earthquakes and tsunamis. The earthquake occurrence is represented by a set of multiple renewal models, which are implemented using a logic-tree approach, whereas earthquake rupture characterization is based on stochastic source models with variable fault geometry and heterogeneous slip distribution. By integrating these hazard components with seismic and tsunami fragility functions, multi-hazard loss potential for a coastal community can be evaluated quantitatively by considering different possibilities of earthquake recurrence and rupture characteristics. To demonstrate the implementation of the developed time-dependent multi-hazard loss model, the Tohoku region of Japan is considered.

Fragility curves for toppling of railroad locomotives

Three locomotives that overturned (toppled) during strong earthquakes (>6.5M) are used as computer analytical case studies. The locomotives were at rest or traveling very slowly at the time of the earthquakes. Fragility curves are presented relating ground shaking intensity to likelihood of toppling. Supplemental studies determine the influence of various parameters, including track gauge, damping, sway-roll period, and size effect. The shaking intensities necessary for standard gauge (56.5 in) locomotives to topple are much greater than the median intensities of 2475-year earthquakes representative of those in high seismic regions of the western United States. A general conclusion is that standard gauge locomotives at rest are not susceptible to toppling in such earthquakes (≪50% chance). This can be expected to be the case as well for freight and passenger cars having sizes and slenderness similar to the case study locomotives. The study also provides insights about the toppling fragility of other large unanchored objects having similar proportions.

Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network

SUMMARY This study describes a deep convolutional neural network (CNN) based technique to predict intensity measurements (IMs) of earthquake ground shaking. The input data to the CNN model consists of multistation, 3C acceleration waveforms recorded during the 2016 Central Italy earthquake sequence for M ≥ 3.0 events. Using a 10 s window starting at the earthquake origin time, we find that the CNN is capable of accurately predicting IMs at stations far from the epicentre which have not yet recorded the maximum ground shaking. The CNN IM predictions do not require previous knowledge of the earthquake source (location and magnitude). Comparison between the CNN model predictions and those obtained with the Bindi et al. GMPE (which requires location and magnitude) shows that the CNN model features similar error variance but smaller bias. Although the technique is not strictly designed for earthquake early warning, we find that it can provide useful estimates of ground motions within 15–20 s after earthquake origin time depending on various setup elements (e.g. times for data transmission, computation, latencies). The technique has been tested on raw data without any initial data pre-selection in order to closely replicate real-time data streaming. When noise examples were included with the earthquake data the CNN was found to be stable, accurately predicting the ground shaking intensity corresponding to the noise amplitude.

Liquefaction, building settlement, and residual strength of two residential areas during the 2016 southern Taiwan earthquake

On February 6, 2016, a moment magnitude (Mw) 6.4 earthquake struck southern Taiwan and devastated the Tainan area. Although the intensity of ground shaking was only moderate (peak ground acceleration, ~ 0.2 g), widespread damage associated with liquefaction (e.g., settlement and tilt of residential buildings) was observed. In this study, soil liquefaction in two residential areas during the Meinong earthquake was assessed comprehensively via field investigation and thorough numerical analysis. Liquefaction triggering analysis using field measurement was performed initially to identify the liquefied layer. The agreement between the gradation of ejecta and in situ soil sample corresponding to the liquefied layer confirmed the analysis results. The liquefied layer is shallow, and the damage level (i.e., settlement) is highly correlated to the distance between the footing and liquefied layer. In the second part of the study, a simplified numerical analysis was proposed to simulate the interaction between the shallow footing structure and liquefied soil. By gradually reducing the soil strength of the liquefied layer in the analysis, the residual strength of the liquefied soil was found to be 10–20% of the original one to reproduce the observed building settlement. The obtained residual strength is compatible with the previous study based on the back analysis of embankment or slope failures.

Design and implementation of a mobile device app for network-based earthquake early warning systems (EEWSs): application to the PRESTo EEWS in southern Italy

Abstract. A fundamental feature of any earthquake early warning system is the ability of rapidly broadcast earthquake information to reach a wide audience of potential end users and stakeholders, in an intuitive, customizable way. Smartphones and other mobile devices are nowadays continuously connected to the Internet and represent the ideal tools for earthquake alerts dissemination to inform a large number of users about the potential damaging shaking of an impending earthquake. Here we present a mobile app (named ISNet EWApp or simply EWApp) for Android devices which can receive the alerts generated by a network-based Early Warning system. Specifically, the app receives the earthquake alerts generated by the PRESTo EEWS, which is currently running on the accelerometric stations of the Irpinia Seismic Network (ISNet) in southern Italy. In the absence of alerts, EWApp displays the standard bulletin of seismic events that have occurred within the network. In the event of a relevant earthquake, the app has a dedicated module to predict the expected ground-shaking intensity and the available lead time at the user's position and to provide customized messages to inform the user about the proper reaction to adopt during the alert. We first present the architecture of both the network-based system and EWApp and then describe its essential operational modes. The app is designed in a way that is easily exportable to any other network-based early warning system.

Seismic vulnerability of circular tunnels in soft soil deposits: The case of Shanghai metropolitan system

This paper aims at the vulnerability assessment of circular tunnels in soft soil deposits of the metropolitan subway system of Shanghai, accounting for the effects of soil-structure-interaction, local soil conditions and tunnel burial depth. The study focuses on the seismic vulnerability in the transversal direction. A suite of twelve earthquake records is selected and scaled from 0.1 g to 1.0 g to perform non-linear incremental dynamic analysis (IDA), and thus to assess the tunnel response under increasing levels of ground shaking intensity. A visco-elasto-plastic model with Mohr-Coulomb yield criterion is adopted to capture the non-linear behaviour of soil deposits under the seismic excitation. Fragility curves are constructed as a function of free-field peak ground acceleration (PGA) and peak ground velocity (PGV) considering the main sources of uncertainties, with the damage measure (DM) being defined in terms of acting over capacity bending moment ratio of the tunnel lining. The derived fragility curves are compared with existing empirical and analytical ones. Furthermore, vulnerability curves are generated from the derived fragility curves. The significant role of local soil conditions and tunnel burial depth in the vulnerability of tunnels in soft and deep alluvial deposits is highlighted. The proposed fragility and vulnerability functions may be particularly used for the risk analysis of circular tunnels in soft deposits (Vs30 < 200 m/s) exposed to seismically-induced transient ground deformations in the transverse direction.

ГИДРОГЕОХИМИЧЕСКИЕ ПРЕДВЕСТНИКИ ЗЕМЛЕТРЯСЕНИЙ (НА ПРИМЕРЕ РАЙОНОВ ПОЛУОСТРОВА КАМЧАТКА, РОССИЯ, И РЕСПУБЛИКИ УЗБЕКИСТАН)

Hydrogeochemical precursors of the earthquakes (HGCP) in changes of ion-salt and gas composition of underground waters from self-discharging wells and springs on the territory of Petropavlovsk-Kamchatsky test site, Kamchatka Peninsula, Russia and Tashkent test site, Republic of Uzbekistan are considered. There has been analyzed the connection of HGCP with parameters of earthquakes — with correlation between magnitudes and epicentral distances, as well as with values of specific density of seismic energy in the wave, intensity of ground shaking and other parameters of earthquake impact in the regions of observation. In Kamchatka wells HGCP were revealed before the earthquakes with Mw = 6.5 to 7.8 at epicentral distances de = 100 to 310 km at relatively narrow ranges of values of seismic energy density in the wave (0.1 to 0.3 J/m3), volumetric coseismic deformation of water-containing rocks (one to tens 10-9) and maximal velocities of seismic waves (3.5–7.7 cm/sec). HGCP took place in the zones with intensity of the earthquakes not less than 4 to 6 by MSK-64 scale and were confined to the intermediate zones of sources of future earthquakes. Duration of HGCP development and their appearance before the following earthquakes amount to 1 to 9 months, which allows using such precursors for prediction of time of strong earthquakes.

Fragility curve of low-to-mid-rise concrete frame retrofitted with FRP

In order to achieve satisfactory global seismic behaviour of a concrete fame structure and to prevent undesirable local failures of its structural element, local strengthening of structural members by means of FRP wrap is one of the cost effective retrofitting strategy. This FRP wrapped column will increase the ductility of the element as well as the capacity that in turn will allow attaining more energy dissipating global performance. This on-going research aims to demonstrate the seismic performance of Low-to-Mid-Rise Concrete Frame retrofitted by FRP wrap in several configurations. The fragility curves of the structure before and after to local strengthening will be developed and analysed. Fragility curve will describe the probability of the structure that will exceed certain damage states given the ground shaking intensity during its service life. This curve allows evaluation for the retrofitting strategy is carried out rationally.

Evaluation of The Seismic Hazard in The Marmara Region (Turkey) Based on Updated Databases

The increase in the wealth of information on the seismotectonic structure of the Marmara region after two devastating earthquakes (M7.6 Izmit and M7.2 Duzce events) in the year 1999 opened the way for the reassessment of the probabilistic seismic hazard in the light of new datasets. In this connection, the most recent findings and outputs of different national and international projects concerning seismicity and fault characterization in terms of geometric and kinematic properties are exploited in the present study to build an updated seismic hazard model. A revised fault segmentation model, alternative earthquake rupture models under a Poisson and renewal assumptions, as well as recently derived global and regional ground motion prediction equations (GMPEs) are put together in the present model to assess the seismic hazard in the region. Probabilistic seismic hazard assessment (PSHA) is conducted based on characteristic earthquake modelling for the fault segments capable of producing large earthquakes and smoothed seismicity modelling for the background smaller magnitude earthquake activity. The time-independent and time-dependent seismic hazard results in terms of spatial distributions of three ground-shaking intensity measures (peak ground acceleration, PGA, and 0.2 s and 1.0 s spectral accelerations (SA) on rock having 10% and 2% probabilities of exceedance in 50 years) as well as the corresponding hazard curves for selected cities are shown and compared with previous studies.

Cascading Geological Hazards and Risks of the 2018 Sulawesi Indonesia Earthquake and Sensitivity Analysis of Tsunami Inundation Simulations

Multiple cascading hazards triggered by the 2018 Sulawesi, Indonesia, earthquake caused various compounding consequences. A major strike-slip fault movement with along-dip components resulted in intense ground shaking, liquefaction and lateral spreading, large-scale mudflows, and tsunamis. This paper presents observations of such multi-hazard effects on buildings and infrastructure in areas along Palu Bay, based on field reconnaissance work, and discusses the main causes of the disaster by focusing upon the combined effects of the cascading geological hazards. To evaluate the tsunami risk potential of the strike-slip event, tsunami simulations for the 2018 Sulawesi earthquake are performed by considering different model settings for spatial earthquake slip distribution, rake angle, astronomical tidal effect, and co-seismic ground deformation. The numerical results indicate that the co-seismic rupture of a moment magnitude 7.5 strike-slip earthquake, having notable dip components can generate damaging tsunami waves at coastal locations of Palu Bay. The conclusion has important implications for future tsunami hazard assessments in active seismic regions where major fault systems cut across a bay or into the sea.

Influence of foundation type on seismic response of low-rise structures in liquefiable soil

The 2010–2011 Canterbury Earthquake Sequence (CES) caused extensive damage to low-rise structures in the city of Christchurch, New Zealand, mainly due to liquefaction-induced effects including settlement and angular distortion. This paper will present the results of dynamic centrifuge tests comparing the effects of liquefaction on the seismic performance of isolated structures with different types of shallow foundations (strips or a raft), and the effect of being situated adjacent to a heavier neighbouring structure of the same foundation type (i.e. considering structure-soil-structure interaction, SSSI). Performance will be evaluated under a sequence of successive earthquakes from the 2010–2011 CES and 2011 Tohoku Earthquake, Japan, to permit study under ground motions and aftershocks generating full liquefaction either extensively or to only a limited depth below ground level. The results show firstly that lower intensity ground shaking occurs at the ground surface when liquefaction occurs and that this can be estimated as a function of the degree of liquefaction using a simple estimation method. When subjected to these ground motions, using strip foundations for isolated structures can result in a reduction in structural demand, especially when the soil is extensively liquefied. When a neighbouring structure with the same foundation type is present, the effects of SSSI within liquefied soil result in changes to natural period and damping such that raft-founded structures exhibited lower structural demands. In either case (isolated or adjacent), a reduction in structural demand is accompanied by an increase in post-earthquake permanent foundation deformation.