Genetic algorithm‐based ground motion selection method matching target distribution of generalized conditional intensity measures

2020 ◽  
Author(s):  
Kun Ji ◽  
Ruizhi Wen ◽  
Chengcai Zong ◽  
Yefei Ren
Keyword(s):  
Genetic Algorithm ◽  
Ground Motion ◽  
Selection Method ◽  
Conditional Intensity ◽  
Intensity Measures ◽  
Target Distribution ◽  
Ground Motion Selection

Consideration and Propagation of Ground Motion Selection Epistemic Uncertainties to Seismic Performance Metrics

2018 ◽  
Vol 34 (2) ◽  
pp. 587-610 ◽  
Author(s):  
Karim Tarbali ◽  
Brendon A. Bradley ◽  
Jack W. Baker
Keyword(s):  
Seismic Hazard ◽  
Seismic Response ◽  
Ground Motion ◽  
Seismic Performance ◽  
Performance Metrics ◽  
Epistemic Uncertainty ◽  
Seismic Demand ◽  
Intensity Measures ◽  
Ground Motion Selection ◽  
The Mean

This paper investigates various approaches to propagate the effect of epistemic uncertainty in seismic hazard and ground motion selection to seismic performance metrics. Specifically, three approaches with different levels of rigor are presented for establishing the conditional distribution of intensity measures considered for ground motion selection, selecting ground motion ensembles, and performing nonlinear response history analyses (RHAs) to probabilistically characterize seismic response. The mean and distribution of the seismic demand hazard is used as the principal means to compare the various results. An example application illustrates that, for seismic demand levels significantly below the collapse limit, epistemic uncertainty in seismic response resulting from ground motion selection can generally be considered as small relative to the uncertainty in the seismic hazard itself. In contrast, uncertainty resulting from ground motion selection appreciably increases the uncertainty in the seismic demand hazard for near-collapse demand levels.

scholarly journals Empirical Correlations between Peak Ground Velocity and Spectrum-Based Intensity Measures

2012 ◽  
Vol 28 (1) ◽  
pp. 17-35 ◽  
Author(s):  
Brendon A. Bradley
Keyword(s):  
Ground Motion ◽  
Peak Ground Velocity ◽  
Strongly Correlated ◽  
Correlation Equations ◽  
Ground Acceleration ◽  
Intensity Measures ◽  
Ground Motion Selection ◽  
Crustal Earthquakes ◽  
Short Period ◽  
Spectrum Intensity

Empirical correlation equations between peak ground velocity ( PGV) and several spectrum-based ground motion intensity measures are developed. The intensity measures examined in particular were: peak ground acceleration ( PGA), 5% damped pseudo-spectral acceleration ( SA), acceleration spectrum intensity ( ASI), and spectrum intensity ( SI). The computed correlations were obtained using ground motions from active shallow crustal earthquakes and four ground motion prediction equations. Results indicate that PGV is strongly correlated (i.e., a correlation coefficient of [Formula: see text]) with SI, moderately correlated with medium to long-period SA (i.e., [Formula: see text] for vibration periods 0.5-3.0 seconds), and also moderately correlated with short period SA, PGA and ASI ([Formula: see text]). A simple example is used to illustrate one possible application of the developed correlation equations for ground motion selection.

Skyline-based ground motion selection method for nonlinear time history analysis of building structures

2012 ◽  
Vol 42 (9) ◽  
pp. 1361-1373 ◽  
Author(s):  
Wei Shi ◽  
Peng Pan ◽  
Lieping Ye ◽  
Yajun Xu ◽  
Chaokun Wang
Keyword(s):  
Ground Motion ◽  
Time History ◽  
Selection Method ◽  
Time History Analysis ◽  
Nonlinear Time History Analysis ◽  
Building Structures ◽  
Ground Motion Selection ◽  
History Analysis ◽  
Nonlinear Time History

SEISMIC RESPONSE PREDICTION AND GROUND MOTION SELECTION BY USING INTENSITY MEASURES FOR BASE ISOLATED BUILDINGS

2019 ◽  
Author(s):  
Tansu GOKCE ◽  
Boris SAHIN ◽  
Engin ORAKDOGEN ◽  
Ercan YUKSEL
Keyword(s):  
Seismic Response ◽  
Ground Motion ◽  
Response Prediction ◽  
Intensity Measures ◽  
Ground Motion Selection
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