Relational database used for ground-motion model development in the NGA-sub project

2021 ◽  
pp. 875529302110552
Author(s):  
Silvia Mazzoni ◽  
Tadahiro Kishida ◽  
Jonathan P Stewart ◽  
Victor Contreras ◽  
Robert B Darragh ◽  
...  
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Data Storage ◽  
Relational Database ◽  
Model Development ◽  
Intensity Measures ◽  
Motion Models ◽  
Ground Motion Model ◽  
Ground Motion Models ◽  
Pseudo Spectral

The Next-Generation Attenuation for subduction zone regions project (NGA-Sub) has developed data resources and ground motion models for global subduction zone regions. Here we describe the NGA-Sub database. To optimize the efficiency of data storage, access, and updating, data resources for the NGA-Sub project are organized into a relational database consisting of 20 tables containing data, metadata, and computed quantities (e.g. intensity measures, distances). A database schema relates fields in tables to each other through a series of primary and foreign keys. Model developers and other users mostly interact with the data through a flatfile generated as a time-stamped output of the database. We describe the structure of the relational database, the ground motions compiled for the project, and the means by which the data can be accessed. The database contains 71,340 three-component records from 1880 earthquakes from seven global subduction zone regions: Alaska, Central America and Mexico, Cascadia, Japan, New Zealand, South America, and Taiwan. These data were processed on a component-specific basis to minimize noise effects in the data and remove baseline drifts. Provided ground motion intensity measures include peak acceleration, peak velocity, and 5%-damped pseudo-spectral accelerations for a range of oscillator periods.

scholarly journals Ground motion models for Arias intensity, cumulative absolute velocity, peak incremental ground velocity, and significant duration in New Zealand

2019 ◽  
Vol 52 (4) ◽  
pp. 193-207 ◽  
Author(s):  
Zach Bullock
Keyword(s):  
New Zealand ◽  
Ground Motion ◽  
Absolute Velocity ◽  
Taupo Volcanic Zone ◽  
Arias Intensity ◽  
Intensity Measures ◽  
Motion Models ◽  
Cumulative Absolute Velocity ◽  
Functional Forms ◽  
Ground Motion Models

This study proposes empirical ground motion models for a variety of non-spectral intensity measures and significant durations in New Zealand. Equations are presented for the prediction of the median and maximum rotated components of Arias intensity, cumulative absolute velocity, cumulative absolute velocity above a 5 cm/s2 acceleration threshold, peak incremental ground velocity, and the 5% to 75% and 5% to 95% significant durations. Recent research has highlighted the usefulness of these parameters in both structural and geotechnical engineering. The New Zealand Strong Motion Database provides the database for regression and includes many earthquakes from all regions of New Zealand with the exceptions of Auckland and Northland, Otago and Southland, and Taranaki. The functional forms for the proposed models are selected using cross validation. The possible influence of effects not typically included in ground motion models for these intensity measures is considered, such as hanging wall effects and basin depth effects, as well as altered attenuation in the Taupo Volcanic Zone. The selected functional forms include magnitude and rupture depth scaling, attenuation with distance, and shallow site effects. Finally, the spatial autocorrelation of the models’ within-event residuals is considered and recommendations are made for developing correlated maps of intensity predictions stochastically.

NESS2.0: An Updated Version of the Worldwide Dataset for Calibrating and Adjusting Ground-Motion Models in Near Source

2021 ◽  
Author(s):  
Sara Sgobba ◽  
Chiara Felicetta ◽  
Giovanni Lanzano ◽  
Fadel Ramadan ◽  
Maria D’Amico ◽  
...  
Keyword(s):  
Ground Motion ◽  
Reference Model ◽  
Hanging Wall ◽  
Strong Motion ◽  
Flat File ◽  
Intensity Measures ◽  
Processing Scheme ◽  
Epicentral Area ◽  
Motion Models ◽  
Ground Motion Model

ABSTRACT We present an extended and updated version of the worldwide NEar-Source Strong-motion (NESS) flat file, which includes an increased number of moderate-to-strong earthquakes recorded in epicentral area, new source metadata and intensity measures, comprising spectral displacements and fling-step amplitudes retrieved from the extended baseline correction processing of velocity time series. The resulting dataset consists of 81 events with moment magnitude≥5.5 and hypocentral depth shallower than 40 km, corresponding to 1189 three-component waveforms, which are selected to have a maximum source-to-site distance within one fault length. Details on the flat files, metadata, and ground-motion parameters, processing scheme, and statistical findings are presented and discussed. The analysis of these data allows recognizing the presence of distinctive features (such as pulse-like waveforms, large vertical components, and hanging-wall effects) that can be exploited to assess their impact on near-source seismic motion. As an example, we use the NESS2.0 dataset for calibrating an empirical correction factor of a regional ground-motion model (GMM) mainly based on far-field records. In this way, we can adjust the median predictions to account for near-source effects not fully captured by the reference model. The final goal of this work is to promote the use of the NESS2 flat file as a tool to disseminate qualified and referenced near-source data and metadata in the light of improving the constraints of GMMs (both empirical and physics-based) close to the source.

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.

Correlation of Spectral Acceleration Values from NGA Ground Motion Models

2008 ◽  
Vol 24 (1) ◽  
pp. 299-317 ◽  
Author(s):  
Jack W. Baker ◽  
Nirmal Jayaram
Keyword(s):  
Ground Motion ◽  
Hazard Analysis ◽  
Single Equation ◽  
Spectral Acceleration ◽  
Ground Motion Selection ◽  
Motion Models ◽  
Attenuation Relationships ◽  
Ground Motion Model ◽  
Analysis Application ◽  
Ground Motion Models

Ground motion models (or “attenuation relationships”) describe the probability distribution of spectral acceleration at an individual period, given a set of predictor variables such as magnitude and distance, but they do not address the correlations between spectral acceleration values at multiple periods or orientations. Those correlations are needed for several calculations related to seismic hazard analysis and ground motion selection. Four NGA models and the NGA ground motion database are used here to measure these correlations, and predictive equations are fit to the results. The equations are valid for periods from 0.01 seconds to 10 seconds, versus similar previous equations that were valid only between 0.05 and 5 seconds and produced unreasonable results if extrapolated. Use of the new NGA ground motion database also facilitates a first study of correlations from intra- and inter-event residuals. Observed correlations are not sensitive to the choice of accompanying ground motion model, and intra-event, inter-event, and total residuals all exhibit similar correlation structure. A single equation is thus applicable for a variety of correlation predictions. A simple example illustrates the use of the proposed equations for one hazard analysis application.

scholarly journals Modification of stochastic ground motion models for matching target intensity measures

2017 ◽  
Vol 47 (1) ◽  
pp. 3-24 ◽  
Author(s):  
Alexandra Tsioulou ◽  
Alexandros A. Taflanidis ◽  
Carmine Galasso
Keyword(s):  
Ground Motion ◽  
Intensity Measures ◽  
Motion Models ◽  
Target Intensity ◽  
Ground Motion Models

scholarly journals Estimating Ground-Motion Models via Bayesian Inference using Stan

2021 ◽  
Author(s):  
Nicolas Kuehn ◽  
Peter Stafford
Keyword(s):  
Bayesian Inference ◽  
Ground Motion ◽  
Programming Language ◽  
Motion Model ◽  
Probabilistic Programming ◽  
Motion Models ◽  
Ground Motion Model ◽  
Computer Environment ◽  
Ground Motion Models

We provide a simple introduction to the estimation of ground-motion models via Bayesian inference and the probabilistic programming language Stan.We show one ca implement a simple ground-motion model in Stan, and how can run the program from the computer environment R.We also show how one can access the results, and plot summaries of estimated parameters.A large number of different Stan models for the development https://github.com/pstafford/StanGMMTutorial.

New conditional, scenario-based, and non-conditional cumulative absolute velocity models for subduction tectonic settings

2021 ◽  
pp. 875529302110438
Author(s):  
Chenying Liu ◽  
Jorge Macedo
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Absolute Velocity ◽  
Engineering Practice ◽  
Spectral Acceleration ◽  
Motion Models ◽  
Velocity Models ◽  
Cumulative Absolute Velocity ◽  
Ground Motion Models ◽  
Subduction Zone Earthquakes

The PEER NGA-Sub ground-motion intensity measure database is used to develop new conditional ground-motion models (CGMMs), a set of scenario-based models, and non-conditional models to estimate the cumulative absolute velocity ([Formula: see text]) of ground motions from subduction zone earthquakes. In the CGMMs, the median estimate of [Formula: see text] is conditioned on the estimated peak ground acceleration ([Formula: see text]), the time-averaged shear-wave velocity in the top 30 m of the soil ([Formula: see text]), the earthquake magnitude ([Formula: see text]), and the spectral acceleration at the period of 1 s ([Formula: see text]). Multiple scenario-based [Formula: see text] models are developed by combining the CGMMs with pseudo-spectral acceleration ([Formula: see text]) ground-motion models (GMMs) for [Formula: see text] and [Formula: see text] to directly estimate [Formula: see text] given an earthquake scenario and site conditions. Scenario-based [Formula: see text] models are capable of capturing the complex ground-motion effects (e.g. soil non-linearity and regionalization effects) included in their underlying [Formula: see text]/[Formula: see text] GMMs. This approach also ensures the consistency of the [Formula: see text] estimates with a [Formula: see text] design spectrum. In addition, two non-conditional [Formula: see text] GMMs are developed using Bayesian hierarchical regressions. Finally, we present comparisons between the developed models. The comparisons show that if non-conditional GMMs are properly constrained, they are consistent with scenario-based GMMs. The [Formula: see text] GMMs developed in this study advance the performance-based earthquake engineering practice in areas affected by subduction zone earthquakes.

Evaluation of Ground‐Motion Models for U.S. Geological Survey Seismic Hazard Models: 2018 Anchorage, Alaska, Mw 7.1 Subduction Zone Earthquake Sequence

2019 ◽  
Vol 91 (1) ◽  
pp. 183-194 ◽  
Author(s):  
Daniel E. McNamara ◽  
Emily Wolin ◽  
Peter M. Powers ◽  
Alison M. Shumway ◽  
Morgan P. Moschetti ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
Subduction Zone ◽  
Ground Motion ◽  
Hazard Model ◽  
Earthquake Sequence ◽  
Geological Survey ◽  
Hazard Models ◽  
Data Set ◽  
Motion Models ◽  
Ground Motion Models

Abstract Instrumental ground‐motion recordings from the 2018 Anchorage, Alaska (Mw 7.1), earthquake sequence provide an independent data set allowing us to evaluate the predictive power of ground‐motion models (GMMs) for intraslab earthquakes associated with the Alaska subduction zone. In this study, we evaluate 15 candidate GMMs using instrumental ground‐motion observations of peak ground acceleration and 5% damped pseudospectral acceleration (0.02–10 s) to inform logic‐tree weights for the update of the U.S. Geological Survey seismic hazard model for Alaska. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function, mean, and standard deviations σ of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Alaska seismic hazard model logic trees. To test logic branches in previous seismic hazard models, we evaluate GMM performance as a function of depth and we demonstrate that some GMMs show improved performance for earthquakes with focal depths greater than 50 km. Ten of the initial 15 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the next update of the Alaska seismic hazard model.

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