Localizing Ground-Motion Models in Volcanic Terranes: Shallow Events at Mt. Etna, Italy, Revisited

2020 ◽  
Vol 110 (6) ◽  
pp. 2843-2861
Author(s):  
Giuseppina Tusa ◽  
Horst Langer ◽  
Raffaele Azzaro
Keyword(s):  
Ground Motion ◽  
Hazard Analysis ◽  
Total Error ◽  
Scaling Law ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Hypocentral Distance ◽  
Motion Models ◽  
Mt Etna ◽  
Ground Motion Models

ABSTRACT We present a set of revised ground-motion models (GMMs) for shallow events at Mt. Etna Volcano. The recent occurrence of damaging events, in particular two of the strongest earthquakes ever instrumentally recorded in the area, has required revising previous GMMs, as these failed to match the observations made for events with local magnitude ML>4.3, above all for sites situated close to the epicenter. The dataset now includes 49 seismic events, with a total of 1600 time histories recorded at distances of up to 100 km, and ML ranging from 3.0 to 4.8. The model gives estimates of peak ground acceleration (both horizontal and vertical), peak ground velocity (both horizontal and vertical), and 5% damped horizontal pseudoacceleration response spectral ordinates up to a period of 4 s. GMMs were developed using the functional form proposed by Boore and Atkinson (2008). Furthermore, with a slightly modified approach, we also considered a regression model using a pseudodepth (h) depending on magnitude according to the scaling law by Azzaro et al. (2017). Both models were applied to hypocentral distance ranges of up to 60 km and up to 100 km, respectively. From the statistical analysis, we found that reducing the maximum distance from the event up to 60 km and introducing a magnitude-dependent pseudodepth improved the model in terms of total error. We compared our results with those derived using the GMMs for shallow events at Mt. Etna found by Tusa and Langer (2016) and for volcanic areas by Lanzano and Luzi (2019). The main differences are observed at short epicentral distances and for higher magnitude events. The use of variable pseudodepth avoids sharp peaks of predicted ground-motion parameters around the epicenter, preventing instabilities when using a GMM in probabilistic seismic hazard analysis.

Ground-motion models for Vrancea intermediate-depth earthquakes

2021 ◽  
pp. 875529302110329
Author(s):  
Elena Florinela Manea ◽  
Carmen Ortanza Cioflan ◽  
Laurentiu Danciu
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Seismic Station ◽  
Moment Magnitude ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Ground Shaking ◽  
Intermediate Depth ◽  
Motion Models ◽  
Ground Motion Models

A newly compiled high-quality ground-shaking dataset of 207 intermediate-depth earthquakes recorded in the Vrancea region of the south-eastern Carpathian mountains in Romania was used to develop region-specific empirical predictive equations for various intensity measures: peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration up to 10 s. Besides common predictor variables (e.g. moment magnitude, depth, hypocentral distance, and site conditions), additional distance scaling parameters were added to describe the specific attenuation pattern observed at the stations located not only on the back and fore but also along the Carpathian arc. In this model, we introduce a proxy measure for the site as the fundamental frequency of resonance to characterize the site response at each recording seismic station beside the soil classes. To additionally reduce the site-to-site variability, a non-ergodic methodology was considered, resulting in a lower standard deviation of about 25%. Statistical evaluation of the newly proposed ground-motion models indicates robust performance compared to regional observations. The model shows significant improvements in describing the spatial variability (at different spectral ordinates), particularly for the fore-arc area of the Carpathians where a deep sedimentary basin is located. Furthermore, the model presented herein improves estimates of ground shaking at longer spectral ordinates (>1 s) in agreement with the observations. The proposed ground-motion models are valid for hypocentral distances less than 500 km, depths over 70 km and within the moment magnitude range of 4.0–7.4.

scholarly journals Seismic Hazard Assessment for the Tianshui Urban Area, Gansu Province, China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenming Wang ◽  
David T. Butler ◽  
Edward W. Woolery ◽  
Lanmin Wang
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Design ◽  
Hazard Analysis ◽  
Seismic Hazard Assessment ◽  
Gansu Province ◽  
Mitigation Measures ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Acceleration Time Histories

A scenario seismic hazard analysis was performed for the city of Tianshui. The scenario hazard analysis utilized the best available geologic and seismological information as well as composite source model (i.e., ground motion simulation) to derive ground motion hazards in terms of acceleration time histories, peak values (e.g., peak ground acceleration and peak ground velocity), and response spectra. This study confirms that Tianshui is facing significant seismic hazard, and certain mitigation measures, such as better seismic design for buildings and other structures, should be developed and implemented. This study shows that PGA of 0.3 g (equivalent to Chinese intensity VIII) should be considered for seismic design of general building and PGA of 0.4 g (equivalent to Chinese intensity IX) for seismic design of critical facility in Tianshui.

Ground-Motion Prediction Model Based on Neural Networks to Extract Site Properties from Observational Records

2021 ◽  
Author(s):  
Tomohisa Okazaki ◽  
Nobuyuki Morikawa ◽  
Asako Iwaki ◽  
Hiroyuki Fujiwara ◽  
Tomoharu Iwata ◽  
...  
Keyword(s):  
Ground Motion ◽  
Ground Acceleration ◽  
Site Specific ◽  
Motion Data ◽  
Motion Models ◽  
Proposed Model ◽  
Single Station ◽  
Input Variables ◽  
Ground Condition ◽  
Ground Motion Models

ABSTRACT Choosing the method for inputting site conditions is critical in reducing the uncertainty of empirical ground-motion models (GMMs). We apply a neural network (NN) to construct a GMM of peak ground acceleration that extracts site properties from ground-motion data instead of referring to ground condition variables given for each site. A key structure of the model is one-hot representations of the site ID, that is, specifying the collection site of each ground-motion record by preparing input variables corresponding to all observation sites. This representation makes the best use of the flexibility of NN to obtain site-specific properties while avoiding overfitting at sites where a small number of strong motions have been recorded. The proposed model exhibits accurate and robust estimations among several compared models in different aspects, including data-poor sites and strong motions from large earthquakes. This model is expected to derive a single-station sigma that evaluates the residual uncertainty under the specification of estimation sites. The proposed NN structure of one-hot representations would serve as a standard ingredient for constructing site-specific GMMs in general regions.

NGA-Subduction research program

2021 ◽  
pp. 875529302110560
Author(s):  
Yousef Bozorgnia ◽  
Norman A Abrahamson ◽  
Sean K Ahdi ◽  
Timothy D Ancheta ◽  
Linda Al Atik ◽  
...  
Keyword(s):  
Ground Motion ◽  
Research Program ◽  
Epistemic Uncertainty ◽  
Specific Model ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Motion Data ◽  
Motion Models ◽  
Aleatory Variability ◽  
Adjustment Factors

This article summarizes the Next Generation Attenuation (NGA) Subduction (NGA-Sub) project, a major research program to develop a database and ground motion models (GMMs) for subduction regions. A comprehensive database of subduction earthquakes recorded worldwide was developed. The database includes a total of 214,020 individual records from 1,880 subduction events, which is by far the largest database of all the NGA programs. As part of the NGA-Sub program, four GMMs were developed. Three of them are global subduction GMMs with adjustment factors for up to seven worldwide regions: Alaska, Cascadia, Central America and Mexico, Japan, New Zealand, South America, and Taiwan. The fourth GMM is a new Japan-specific model. The GMMs provide median predictions, and the associated aleatory variability, of RotD50 horizontal components of peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration (PSA) at oscillator periods ranging from 0.01 to 10 s. Three GMMs also quantified “within-model” epistemic uncertainty of the median prediction, which is important in regions with sparse ground motion data, such as Cascadia. In addition, a damping scaling model was developed to scale the predicted 5%-damped PSA of horizontal components to other damping ratios ranging from 0.5% to 30%. The NGA-Sub flatfile, which was used for the development of the NGA-Sub GMMs, and the NGA-Sub GMMs coded on various software platforms, have been posted for public use.

Ranking of Ground-Motion Models (GMMs) for Use in Probabilistic Seismic Hazard Analysis for Iran Based on an Independent Data Set

2020 ◽  
Author(s):  
Zoya Farajpour ◽  
Milad Kowsari ◽  
Shahram Pezeshk ◽  
Benedikt Halldorsson
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Selection Process ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Data Set ◽  
Motion Models ◽  
Ground Motion Models

ABSTRACT We apply three data-driven selection methods, log-likelihood (LLH), Euclidean distance-based ranking (EDR), and deviance information criterion (DIC), to objectively evaluate the predictive capability of 10 ground-motion models (GMMs) developed from Iranian and worldwide data sets against a new and independent Iranian strong-motion data set. The data set includes, for example, the 12 November 2017 Mw 7.3 Ezgaleh earthquake and the 25 November 2018 Mw 6.3 Sarpol-e Zahab earthquake and includes a total of 201 records from 29 recent events with moment magnitudes 4.5≤Mw≤7.3 with distances up to 275 km. The results of this study show that the prior sigma of the GMMs acts as the key measure used by the LLH and EDR methods in the ranking against the data set. In some cases, this leads to the resulting model bias being ignored. In contrast, the DIC method is free from such ambiguity as it uses the posterior sigma as the basis for the ranking. Thus, the DIC method offers a clear advantage of partially removing the ergodic assumption from the GMM selection process and allows a more objective representation of the expected ground motion at a specific site when the ground-motion recordings are homogeneously distributed in terms of magnitudes and distances. The ranking results thus show that the local models that were exclusively developed from Iranian strong motions perform better than GMMs from other regions for use in probabilistic seismic hazard analysis in Iran. Among the Next Generation Attenuation-West2 models, the GMMs by Boore et al. (2014) and Abrahamson et al. (2014) perform better. The GMMs proposed by Darzi et al. (2019) and Farajpour et al. (2019) fit the recorded data well at short periods (peak ground acceleration and pseudoacceleration spectra at T=0.2  s). However, at long periods, the models developed by Zafarani et al. (2018), Sedaghati and Pezeshk (2017), and Kale et al. (2015) are preferable.

Exploring the Proximity of Ground-Motion Models Using High-Dimensional Visualization Techniques

2010 ◽  
Vol 26 (4) ◽  
pp. 1117-1138 ◽  
Author(s):  
Frank Scherbaum ◽  
Nicolas M. Kuehn ◽  
Matthias Ohrnberger ◽  
Andreas Koehler
Keyword(s):  
Ground Motion ◽  
Hazard Analysis ◽  
Ground Motions ◽  
High Dimensional ◽  
Logic Tree ◽  
Motion Models ◽  
Metric Set ◽  
Motion Characteristics ◽  
Visualization Techniques ◽  
Ground Motion Models

Logic trees have become a popular tool to capture epistemic uncertainties in seismic hazard analysis. They are commonly used by assigning weights to models on a purely descriptive basis (nominal scale). This invites the creation of unintended inconsistencies regarding the weights on the corresponding hazard curves. On the other hand, for human experts it is difficult to confidently express degrees-of-beliefs in particular numerical values. Here we demonstrate for ground-motion models how the model and the value-based perspectives can be partially reconciled by using high-dimensional information-visualization techniques. For this purpose we use Sammon's (1969) mapping and self-organizing mapping to project ground-motion models onto a two-dimensional map (an ordered metric set). Here they can be evaluated jointly according to their proximity in predicting similar ground motions, potentially making the assignment of logic tree weights consistent with their ground motion characteristics without having to abandon the model-based perspective.

scholarly journals New Ground Motion to Intensity Conversion Equations for China

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xiufeng Tian ◽  
Zengping Wen ◽  
Weidong Zhang ◽  
Jie Yuan
Keyword(s):  
Ground Motion ◽  
Correction Term ◽  
Strong Motion ◽  
Seismic Intensity ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Strong Earthquakes ◽  
Hypocentral Distance ◽  
Peak Ground Motion ◽  
Pseudo Spectral

In this study, we use the strong motion records and seismic intensity data from 11 moderate-to-strong earthquakes in the mainland of China since 2008 to develop new conversion equations between seismic intensity and peak ground motion parameters. Based on the analysis of the distribution of the dataset, the reversible conversion relationships between modified Mercalli intensity (MMI) and peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo-spectral acceleration (PSA) at natural vibration periods of 0.3 s, 1.0 s, 2.0 s, and 3.0 s are obtained by using the orthogonal regression. The influence of moment magnitude, hypocentral distance, and hypocentral depth on the residuals of conversion equations is also explored. To account for and eliminate the trends in the residuals, we introduce a magnitude-distance-depth correction term and obtain the improved relationships. Furthermore, we compare the results of this study with previously published works and analyze the regional dependence of conversion equations. To quantify the regional variations, a regional correction factor for China, suitable for adjustment of global relationships, has also been estimated.

Relationships between ground motion parameters and damaged buildings for 2016 Mw 6.4 Meinong, Taiwan Earthquake

2020 ◽  
Author(s):  
Guan-Yi Song ◽  
Yih-Min Wu
Keyword(s):  
Ground Motion ◽  
Peak Ground Acceleration ◽  
Hazard Analysis ◽  
Assessment System ◽  
Peak Ground Velocity ◽  
Current Status ◽  
Ground Acceleration ◽  
Ground Motion Parameters ◽  
Motion Parameters ◽  
Seismic Damage Assessment

<p>The relationships between ground motion parameters (including peak ground acceleration, PGA; peak ground velocity, PGV) and building damages are crucial to estimate the possible seismic losses for future destructive earthquakes. One such relationship had been established based on the 1999 Chi-Chi earthquake (Mw=7.6). Since 2010, a new assessment system of seismic damaged buildings had been adopted in Taiwan. Damaged buildings are now classified into two categories, yellow-tagged buildings are amendable and red-tagged buildings may need to rebuild. Our main goal is to renew the relationship to better reflect the current status in Taiwan, both in the buildings and assessment system. 2016 Meinong earthquake (Mw=6.4) caused the most damaging buildings in Taiwan since 1999 Chi-Chi earthquake. It’s an opportunity to combine ground motion data with building assessments for the new regression relationship. From the results, we find out that in the Meinong earthquake, the PGA seems to possess a higher correlation to the building damages, contrary to the previous studies. Further investigation suggests that it may be due to the biased sample size to the damaged buildings, that is, most of the damaged buildings tend to be lower.</p><p>Keywords: Hazard analysis, Peak ground acceleration, Peak ground velocity, Seismic damage assessment</p>

scholarly journals Characteristics of strong ground motion attenuation in the 2019 Mw 5.8 Changning earthquake, Sichuan, China

2021 ◽  
Author(s):  
J. J. Hu ◽  
H. Zhang ◽  
J. B. Zhu ◽  
G. H. Liu
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Response Spectra ◽  
Peak Ground Velocity ◽  
Arias Intensity ◽  
Ground Acceleration ◽  
Motion Models ◽  
Ground Motion Attenuation ◽  
Short Period ◽  
Strong Ground

AbstractA moderate magnitude earthquake with Mw 5.8 occurred on June 17, 2019, in Changning County, Sichuan Province, China, causing 13 deaths, 226 injuries, and serious engineering damage. This earthquake induced heavier damage than earthquakes of similar magnitude. To explain this phenomenon in terms of ground motion characteristics, based on 58 sets of strong ground motions in this earthquake, the peak ground acceleration (PGA), peak ground velocity (PGV), acceleration response spectra (Sa), duration, and Arias intensity are analyzed. The results show that the PGA, PGV, and Sa are larger than the predicted values from some global ground motion models. The between-event residuals reveal that the source effects on the intermediate-period and long-period ground motions are stronger than those on short-period ground motions. Comparison of Arias intensity attenuation with the global models indicates that the energy of ground motions of the Changning earthquake is larger than those of earthquakes with the same magnitude.

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