An Overview of the NGA Project

2008 ◽  
Vol 24 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Maurice Power ◽  
Brian Chiou ◽  
Norman Abrahamson ◽  
Yousef Bozorgnia ◽  
Thomas Shantz ◽  
...  
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Research Program ◽  
Development Process ◽  
Strong Motion ◽  
Engineering Research ◽  
Motion Models ◽  
Ground Motion Attenuation ◽  
Attenuation Models ◽  
Ground Motion Models

The “Next Generation of Ground-Motion Attenuation Models” (NGA) project is a multidisciplinary research program coordinated by the Lifelines Program of the Pacific Earthquake Engineering Research Center (PEER), in partnership with the U.S. Geological Survey and the Southern California Earthquake Center. The objective of the project is to develop new ground-motion prediction relations through a comprehensive and highly interactive research program. Five sets of ground-motion models were developed by teams working independently but interacting with one another throughout the development process. The development of ground-motion models was supported by other project components, which included (1) developing an updated and expanded PEER database of recorded ground motions, including supporting information on the strong-motion record processing, earthquake sources, travel path, and recording station site conditions; (2) conducting supporting research projects to provide guidance on the selected functional forms of the ground-motion models; and (3) conducting a program of interactions throughout the development process to provide input and reviews from both the scientific research and engineering user communities. An overview of the NGA project components, process, and products is presented in this paper.

Conditional Ground-Motion Models for Horizontal Peak Ground Displacement for Active Crustal Regions

2021 ◽  
Author(s):  
Chih-Hsuan Sung ◽  
Norman A. Abrahamson ◽  
Jyun-Yan Huang
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Input Parameter ◽  
Strong Motion ◽  
Tectonic Deformation ◽  
Ground Displacement ◽  
Strong Motion Data ◽  
Motion Data ◽  
Motion Models ◽  
Ground Motion Models

ABSTRACT Ground-motion models (GMMs) are developed for peak ground displacement (PGD) and for bandlimited PGD based on strong-motion data that has been filtered as part of standard processing and the total PGD that includes the tectonic deformation as well as the vibratory ground motion. For the bandlimited PGD, we develop conditional ground-motion models (CGMMs) using subsets of the Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 Project (NGA-W2) database and the National Center for Research on Earthquake Engineering Taiwan Senior Seismic Hazard Analysis Committee level 3 project database. The CGMM approach includes the observed pseudospectral acceleration (PSA(T)) as an input parameter in addition to magnitude and distance. The period of the PSA(T) is used as an input parameter; it is magnitude dependent and is based on the period for which there is the highest correlation between the ln(PGD) and ln(PSA(T)). Two CGMMs are developed: a global model based on the NGA-W2 data and a region-specific model for Taiwan. The conditional PGD models are combined with traditional GMMs for PSA(T) values to develop GMMs for both the median and standard deviation of PGD without the dependence on PSA. A second set of PGD GMMs are developed to correct for two factors: the effect of the high-pass filtering from standard record processing and the stronger large magnitude (M>6.5) scaling due to tectonic deformation. For magnitudes greater than 7, the PGD values from the total PGD GMMs are 2–5 times larger than the bandlimited PGD values based on the strong-motion data sets, but the increase is at very long periods. The appropriate PGD model to use, bandlimited PGD or total PGD, depends on the period range of interest for the specific engineering application.

The 2018 national seismic hazard assessment of Australia: Quantifying hazard changes and model uncertainties

2020 ◽  
Vol 36 (1_suppl) ◽  
pp. 5-43 ◽  
Author(s):  
Trevor I Allen ◽  
Jonathan D Griffin ◽  
Mark Leonard ◽  
Dan J Clark ◽  
Hadi Ghasemi
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Assessment ◽  
Seismic Hazard Assessment ◽  
Earthquake Catalog ◽  
Motion Models ◽  
Ground Motion Attenuation ◽  
Attenuation Models ◽  
Instrumental Period ◽  
Ground Motion Models

Seismic hazard assessments in stable continental regions such as Australia face considerable challenges compared with active tectonic regions. Long earthquake recurrence intervals relative to historical records make forecasting the magnitude, rates, and locations of future earthquakes difficult. Similarly, there are few recordings of strong ground motions from moderate-to-large earthquakes to inform development and selection of appropriate ground-motion models (GMMs). Through thorough treatment of these epistemic uncertainties, combined with major improvements to the earthquake catalog, a 2018 National Seismic Hazard Assessment (NSHA18) of Australia has been undertaken. The resulting hazard levels at the 10% in 50-year probability of exceedance level are in general significantly lower than previous assessments, including hazard factors used in the Australian earthquake loading standard ( AS 1170.4–2007 (R2018)), demonstrating our evolving understanding of seismic hazard in Australia. The key reasons for the decrease in seismic hazard factors are adjustments to catalog magnitudes for earthquakes in the early instrumental period, and the use of modern ground-motion attenuation models. This article summarizes the development of the NSHA18 explores uncertainties associated with the hazard model, and identifies the dominant factors driving the resulting changes in hazard compared with previous assessments.

A Suite of Alternative Ground-Motion Models (GMMs) for Israel

2021 ◽  
Author(s):  
Soumya Kanti Maiti ◽  
Gony Yagoda-Biran ◽  
Ronnie Kamai
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Empirical Data ◽  
Epistemic Uncertainty ◽  
Ground Motions ◽  
Plate Boundary ◽  
Strong Motion ◽  
Engineering Applications ◽  
Motion Models ◽  
Ground Motion Models

ABSTRACT Models for estimating earthquake ground motions are a key component in seismic hazard analysis. In data-rich regions, these models are mostly empirical, relying on the ever-increasing ground-motion databases. However, in areas in which strong-motion data are scarce, other approaches for ground-motion estimates are sought, including, but not limited to, the use of simulations to replace empirical data. In Israel, despite a clear seismic hazard posed by the active plate boundary on its eastern border, the instrumental record is sparse and poor, leading to the use of global models for hazard estimation in the building code and all other engineering applications. In this study, we develop a suite of alternative ground-motion models for Israel, based on an empirical database from Israel as well as on four data-calibrated synthetic databases. Two host models are used to constrain model behavior, such that the epistemic uncertainty is captured and characterized. Despite the lack of empirical data at large magnitudes and short distances, constraints based on the host models or on the physical grounds provided by simulations ensure these models are appropriate for engineering applications. The models presented herein are cast in terms of the Fourier amplitude spectra, which is a linear, physical representation of ground motions. The models are suitable for shallow crustal earthquakes; they include an estimate of the median and the aleatory variability, and are applicable in the magnitude range of 3–8 and distance range of 1–300 km.

Are Near-Fault Fling Effects Captured in the New NGA West2 Ground Motion Models?

2015 ◽  
Vol 31 (3) ◽  
pp. 1629-1645 ◽  
Author(s):  
Ronnie Kamai ◽  
Norman Abrahamson
Keyword(s):  
Ground Motion ◽  
Vertical Component ◽  
Strong Motion ◽  
Motion Processing ◽  
Large Set ◽  
Pass Filter ◽  
Motion Models ◽  
Finite Fault ◽  
Maximum Period ◽  
Ground Motion Models

We evaluate how much of the fling effect is removed from the NGA database and accompanying GMPEs due to standard strong motion processing. The analysis uses a large set of finite-fault simulations, processed with four different high-pass filter corners, representing the distribution within the PEER ground motion database. The effects of processing on the average horizontal component, the vertical component, and peak ground motion values are evaluated by taking the ratio between unprocessed and processed values. The results show that PGA, PGV, and other spectral values are not significantly affected by processing, partly thanks to the maximum period constraint used when developing the NGA GMPEs, but that the bias in peak ground displacement should not be ignored.

scholarly journals Seismic hazard evaluation

2000 ◽  
Vol 33 (3) ◽  
pp. 371-386 ◽  
Author(s):  
Paul Somerville
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Ground Motions ◽  
Strong Motion ◽  
Earthquake Source ◽  
Hazard Evaluation ◽  
Data Set ◽  
Motion Models ◽  
The Past ◽  
Ground Motion Models

This paper reviews concepts and trends in seismic hazard characterization that have emerged in the past decade, and identifies trends and concepts that are anticipated during the coming decade. New methods have been developed for characterizing potential earthquake sources that use geological and geodetic data in conjunction with historical seismicity data. Scaling relationships among earthquake source parameters have been developed to provide a more detailed representation of the earthquake source for ground motion prediction. Improved empirical ground motion models have been derived from a strong motion data set that has grown markedly over the past decade. However, these empirical models have a large degree of uncertainty because the magnitude - distance - soil category parameterization of these models often oversimplifies reality. This reflects the fact that other conditions that are known to have an important influence on strong ground motions, such as near- fault rupture directivity effects, crustal waveguide effects, and basin response effects, are not treated as parameters of these simple models. Numerical ground motion models based on seismological theory that include these additional effects have been developed and extensively validated against recorded ground motions, and used to estimate the ground motions of past earthquakes and predict the ground motions of future scenario earthquakes. The probabilistic approach to characterizing the ground motion that a given site will experience in the future is very compatible with current trends in earthquake engineering and the development of building codes. Performance based design requires a more comprehensive representation of ground motions than has conventionally been used. Ground motions estimates are needed at multiple annual probability levels, and may need to be specified not only by response spectra but also by suites of strong motion time histories for input into time-domain non-linear analyses of structures.

NGA-West2 Research Project

2014 ◽  
Vol 30 (3) ◽  
pp. 973-987 ◽  
Author(s):  
Yousef Bozorgnia ◽  
Norman A. Abrahamson ◽  
Linda Al Atik ◽  
Timothy D. Ancheta ◽  
Gail M. Atkinson ◽  
...  
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Research Program ◽  
Epistemic Uncertainty ◽  
Response Spectra ◽  
Site Amplification ◽  
Earthquake Hazards ◽  
Research Project ◽  
Engineering Research ◽  
Crustal Earthquakes

The NGA-West2 project is a large multidisciplinary, multi-year research program on the Next Generation Attenuation (NGA) models for shallow crustal earthquakes in active tectonic regions. The research project has been coordinated by the Pacific Earthquake Engineering Research Center (PEER), with extensive technical interactions among many individuals and organizations. NGA-West2 addresses several key issues in ground-motion seismic hazard, including updating the NGA database for a magnitude range of 3.0–7.9; updating NGA ground-motion prediction equations (GMPEs) for the “average” horizontal component; scaling response spectra for damping values other than 5%; quantifying the effects of directivity and directionality for horizontal ground motion; resolving discrepancies between the NGA and the National Earthquake Hazards Reduction Program (NEHRP) site amplification factors; analysis of epistemic uncertainty for NGA GMPEs; and developing GMPEs for vertical ground motion. This paper presents an overview of the NGA-West2 research program and its subprojects.

Prediction of Ground-Motion Parameters for the NGA-West2 Database Using Refined Second-Order Deep Neural Networks

2021 ◽  
Author(s):  
Duofa Ji ◽  
Chenxi Li ◽  
Changhai Zhai ◽  
You Dong ◽  
Evangelos I. Katsanos ◽  
...  
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Hazard Analysis ◽  
A Priori ◽  
Absolute Error ◽  
Second Order ◽  
Prediction Errors ◽  
Intensity Measures ◽  
Engineering Research ◽  
Motion Models

ABSTRACT One of the key elements within seismic hazard analysis is the establishment of appropriate ground-motion models (GMMs), which are used to predict the levels of ground-motion intensities by considering various parameters (e.g., source, path, and site). Many empirical GMMs were derived on the basis of a predefined linear or nonlinear equation that is heavily dependent on the a priori knowledge of a functional form that varies between the modelers’ choices. To overcome this issue, this study develops a deep neural network (DNN) trained by the recordings from the Pacific Earthquake Engineering Research Center (PEER) Next Generation Attenuation-West2 Project (NGA-West2) database. To this end, we collected 20,900 ground motion recordings from the database and randomly split them into the training, validation, and testing datasets. The refined second-order neuron is proposed to solve the problem, and the Adam optimizer is used to optimize the performance of the model. The prediction errors are evaluated by three performance indicators (i.e., R2, root mean square error, mean absolute error), and the predictive results are compared with previous GMMs developed based on the PEER NGA-West2 database. The between-event and within-event standard deviations (SDs) as well as total SDs are calculated and compared. Based on the comparisons, our model maintains consistent performance (e.g., the dependence of predicted intensity measures on seismological and site-specific parameters) with the compared GMM. Its relatively small total SDs, especially for longer periods, confirm that the proposed model is associated with better predictive power.

Residual analysis of large strong-motion flatfiles as a tool for detecting data error and anomalies

2021 ◽  
Author(s):  
Claudia Mascandola ◽  
Giovanni Lanzano ◽  
Francesca Pacor
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Epistemic Uncertainty ◽  
Strong Motion ◽  
Consistency Check ◽  
Mixed Effect ◽  
Motion Models ◽  
Tree Classifier ◽  
The Common ◽  
Ground Motion Models

<p>The rapid increase of seismic waveforms, due to the increment of seismic stations and continuous real-time streaming to data centres, leads to the need for automatic procedures aimed at supporting data processing and data quality control. In this study, we propose a semi-automatic procedure for the consistency check of large strong-motion datasets, classifying the anomalies observed on the residuals analysis and identifying the possible causes.</p><p>The data collected in the strong-motion databases are usually arranged as parametric tables (called flatfiles), used to disseminate the Intensity Measures (IMs) and the associated metadata of the processed waveforms. This is the current practice for the ITalian ACcelerometric Archive (ITACA, D’Amico et al., 2020) and Engineering Strong Motion (ESM; Lanzano et al. 2019a) databases. The adopted criteria for flatfile compilation are designed to collect IMs and related metadata in a uniform, updated, and traceable way, with the aim of providing datasets useful to develop Ground Motion Models (GMMs) for Probabilistic Seismic Hazard Assessment (PSHA) and engineering applications. Therefore, the consistency check of the flatfiles is a crucial task to improve the quality of the products provided by the waveform services.</p><p>The proposed procedure is based on the residual distributions obtained from ad-hoc ground motion prediction equations for the ordinates of the 5% damped acceleration response spectra. In this study, we focus on the active shallow crust events in ITACA, considering the ITA18 ground motion model (Lanzano et al., 2019b) as a reference for Italy. The total residuals, computed as logarithm difference between observations and predictions, are decomposed in between-event, between-station and event-and-station corrected residuals by applying a mixed-effect regression (Bates et al., 2015). This is the common practice for the (partial) removal of the ergodic assumption in empirical GMMs (e.g., Stafford 2014), where the contribution of the systematic corrective effects of event and station on aleatory variability are identified and shifted to the epistemic uncertainty. Afterward, the proposed procedure is applied to raise a warning in case of anomalous residual values. Warnings are provided when the normalized residuals exceed a certain threshold, in three ranges of periods (i.e., 0.01-0.15 s, 0.15-1 s, 1-5 s). The causes of warnings may be several and may concern the event, the site, the waveform, or a combination of them. Among the possible sources of anomalous trends, the more common are: preliminary or inaccurate event localization or magnitude, wrong soil category assigned based on proxies, misleading tectonic regime assigned to the earthquake, and fault directivity that may cause strong-ground motion amplification in certain directions. Warnings may also raise for peculiarities in the site-response (e.g., large amplifications/de-amplifications at certain frequency-bands) and to the occurrence of near-source effects in the waveforms (see Pacor et al., 2018). Based on the raised warnings, a decision tree classifier is developed to identify the common anomaly sources and to support the consistency check of the semi-automatic procedure.</p><p>This study may help to enhance the waveform services and related products, besides reducing the variability of ground motion models and guiding decisions for site characterization studies and network maintenance.</p>

Ground Motion Models for the Horizontal Components of Arias Intensity (AI) and Cumulative Absolute Velocity (CAV) Using the NGA-West2 Database

2019 ◽  
Vol 35 (3) ◽  
pp. 1289-1310 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Goodness Of Fit ◽  
Performance Metrics ◽  
Absolute Velocity ◽  
Arias Intensity ◽  
Intensity Measures ◽  
Motion Models ◽  
Cumulative Absolute Velocity ◽  
Ground Motion Models

We updated our Next Generation Attenuation (NGA)-West1 ground motion models (GMMs) for the horizontal components of Arias intensity (AI) and cumulative absolute velocity (CAV) using the functional form and NGA-West2 database we used to develop GMMs for peak-amplitude and peak-spectral ground motion intensity measures (GMIMs). Our results show that CAV has the best goodness-of-fit statistics of all the GMIMs we have evaluated up to this time. Its relatively small between- and within-event standard deviations confirm its superior predictability. On the other hand, AI has the highest standard deviation of any GMIM we have studied thus far, which is approximately double that of CAV. Although either CAV or AI or a combination of both have been shown to meet various performance metrics proposed in the context of performance-based earthquake engineering (PBEE), CAV's high level of predictability makes it superior to AI for use in engineering applications, such as PBEE, that involve probabilistic inference.

Ground-Motion Models for the Prediction of Significant Duration Using Strong-Motion Data from Iran

2020 ◽  
Vol 110 (1) ◽  
pp. 319-330 ◽  
Author(s):  
Ali Meimandi-Parizi ◽  
Masoud Daryoushi ◽  
Abbas Mahdavian ◽  
Hamid Saffari
Keyword(s):  
Ground Motion ◽  
Earthquake Engineering ◽  
Functional Form ◽  
Prediction Models ◽  
Strong Motion ◽  
Engineering Research ◽  
Significant Duration ◽  
Rate Of Increase ◽  
Peer Models ◽  
Rupture Distance

ABSTRACT In this study, new prediction equations for significant duration (DS5–75 and DS5–95) are developed using an Iranian strong ground-motion database. The database includes 2228 records of 749 earthquakes with small to large magnitudes up to the year 2018. The functional form of the model is an additive natural logarithm of four predictor variables, namely moment magnitude (Mw), rupture distance (Rrup), time-averaged shear-wave velocity in the top 30 m (VS30), and the style of faulting effect (Fm), which is considered as an indicator directly in the functional form for the first time. The proposed models can be used to estimate significant durations of earthquakes with moment magnitudes (Mw) from 4.5 to 7.6 and rupture distances of up to 200 km. The models are compared with four existing significant-duration prediction models. The results indicate proper agreement between the proposed models and the models that use the Pacific Earthquake Engineering Research Center-Next Generation Attenuation-West2 Project (PEER-NGA West2) database (say PEER models). Based on the results, our proposed models indicate an increasing trend of significant duration with an increase in the rupture distance. However, unlike the PEER models, the rate of increase in significant duration is decreasing in our model.

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