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

2021 ◽  
pp. 875529302110438
Author(s):  
Chenying Liu ◽  
Jorge Macedo

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.

Author(s):  
Zach Bullock

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.


2019 ◽  
Vol 35 (3) ◽  
pp. 1289-1310 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Yousef Bozorgnia

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.


2021 ◽  
pp. 875529302110552
Author(s):  
Silvia Mazzoni ◽  
Tadahiro Kishida ◽  
Jonathan P Stewart ◽  
Victor Contreras ◽  
Robert B Darragh ◽  
...  

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.


2008 ◽  
Vol 24 (1) ◽  
pp. 299-317 ◽  
Author(s):  
Jack W. Baker ◽  
Nirmal Jayaram

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.


2019 ◽  
Vol 109 (4) ◽  
pp. 1343-1357 ◽  
Author(s):  
Jorge Macedo ◽  
Norman Abrahamson ◽  
Jonathan D. Bray

Abstract Conditional ground‐motion models (CGMMs) for estimating Arias intensity (IA) for earthquakes in subduction zones are developed. The estimate of IA is conditioned in these models on the estimated peak ground acceleration (PGA), the spectral acceleration at T=1  s (SA1), time‐averaged shear‐wave velocity in the top 30 m (VS30), and magnitude (Mw). Random‐effects regressions are used to develop CGMMs for Japan, Taiwan, South America, and New Zealand. By combining the conditional models of IA with the ground‐motion models (GMMs) for PGA and SA1, the conditional models are converted to scenario‐based GMMs that can be used to estimate the median IA and its standard deviation directly for a given earthquake scenario and site conditions. The conditional scaling approach ensures the estimated IA values are consistent with a design spectrum that may correspond to above‐average spectral values for the controlling scenario. In addition, this approach captures the complex ground‐motion scaling effects found in GMMs for spectral acceleration, such as sediment‐depth effects, soil nonlinearity effects, and regionalization effects, in the developed scenario‐based models for IA. Estimates from the new scenario‐based IA models are compared to those from traditional GMMs for IA in subduction zones.


Author(s):  
Jorge Macedo ◽  
Norman Abrahamson ◽  
Chenying Liu

ABSTRACT The Pacific Earthquake Engineering Research Center Next Generation Attenuation-West2 database is used to derive a new conditional ground-motion model (CGMM) and a set of scenario-based models for estimating cumulative absolute velocity (CAV) for earthquakes in shallow crustal tectonic settings. Random-effects regressions were performed to develop the conditional model, with random effects across different earthquakes. The estimate of CAV is conditioned on the estimated peak ground acceleration (PGA), the time averaged shear-wave velocity in the top 30 m (VS30), the earthquake magnitude (Mw), and the rupture distance (Rrup). By combining the conditional CAV model with ground-motion models (GMM) in shallow crustal earthquake zones for PGA, new scenario-based models are developed for estimating the median CAV and its standard deviation, directly from an earthquake scenario and site conditions. A scenario-based CAV model captures inherently the complex ground-motion scaling effects included in the GMMs for spectral accelerations on which it is based on, such as, sediment-depth effects, soil nonlinearity effects, and regionalization effects. This approach also ensures consistency between the estimated CAV values and a design spectral acceleration response spectrum. The conditional and scenario-based models to estimate CAV are presented, and trends of the developed scenario-based models and previous traditional models for CAV are compared. Interestingly, we found a remarkable consistency between scenario-based and traditional nonconditional CAV models, when the underlain spectral GMM used in the implementation of the scenario-based model is properly constrained. Finally, we provide examples for the use of the conditional and scenario-based models in performance-based earthquake engineering.


2021 ◽  
Author(s):  
Rahman Tauhidur ◽  
Ricky L Chhangte

Abstract This article presented ground motion model (GMM) for vertical peak ground acceleration (PGA) and pseudo spectral acceleration (Sa) at 5 % damping for North-east India (NEI) and adjacent regions at a time period of 0.01 to 5 s, and hypocentral distance 40 to 300 km. We used combined point source (4.5 ≤ Mw ≤ 6.5) and finite fault model (6.5 < Mw ≤ 9.5) (refer as combined model) to develop GMM for vertical component of ground motion (VCGM) for the region. The vertical GMM obtained is validated with the available recorded events in NEI and adjacent regions for the interface subduction zone earthquakes. It is observed that peak ground accelerations and spectral accelerations are 55 to 65% lesser than the horizontal components of ground motions. VCGM parameters obtained in this study play an important role in designing low rise buildings and linear superstructures such as bridges, silos and chimneys.


Author(s):  
Jorge Macedo ◽  
Chenying Liu

ABSTRACT The NGA-Sub (subduction zone earthquake) database developed by the Pacific Earthquake Engineering Research center is used to derive new correlation coefficients for a number of ground-motion intensity measure (IM) parameters from ground motions in subduction zone earthquakes, considering both interface and intraslab tectonic settings. The IMs include peak ground acceleration, pseudospectral accelerations with periods from 0.01 to 10 s, Arias intensity, cumulative absolute velocity, peak ground velocity, and significant duration. Comparisons of the estimated correlation coefficients for ground motions from the interface and intraslab tectonic settings generally show a good agreement. Our estimations are also in good agreement with correlation coefficients estimated in previous studies that used ground motions from shallow crustal earthquakes, supporting the concept that any variation in correlation coefficients comes from spectral shape (i.e., the distribution of peaks and troughs) rather than tectonic region. This study also explores the influence of parameters such as magnitude, distance, and site conditions on the estimated correlation coefficients. We did not find apparent trends of the correlation coefficients with respect to these parameters. Finally, we propose analytical models to estimate correlation coefficients between the IMs explored in this study, considering both subduction interface and intraslab tectonic settings.


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