Canonical Correlation Analysis of Selecting Optimal Ground Motion Intensity Measures for Bridges

Song, Seung Yeon; Cong, Qian; Yong-jiu, Qian; Bao, Han; Lin, Pengzhen

doi:10.1007/s12205-019-0929-x

Cited by 8 publications

(3 citation statements)

References 46 publications

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“…It has been instrumented as part of the Strong Motion Instrumentation Program for six-floor and 13-floor buildings [41][42][43]. Additionally, Song et al [44] examined ground motion intensity measures and component seismic demand parameters to conduct a probabilistic seismic demand analysis of bridges. In the study, we used the Opensees to carry out the nonlinear dynamic analysis and perform the Newmark beta method for structural analysis.…”

Section: Six-floor Building Analysis For Development Of the Rapid Prediction Modelmentioning

confidence: 99%

Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment

Park

Jung

2021

IJGI

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Seismic activities are serious disasters that induce natural hazards resulting in an incalculable amount of damage to properties and millions of deaths. Typically, seismic risk assessment can be performed by means of structural damage information computed based on the maximum displacement of the structure. In this study, machine learning models based on GPR are developed in order to estimate the maximum displacement of the structures from seismic activities and then used to construct fragility curves as an application. During construction of the models, 13 features of seismic waves are considered, and six wave features are selected to establish the seismic models with the correlation analysis normalizing the variables with the peak ground acceleration. Two models for six-floor and 13-floor buildings are developed, and a sensitivity analysis is performed to identify the relationship between prediction accuracy and sampling size. A 10-fold cross-validation method is used to evaluate the model performance, using the R-squared, root mean squared error, Nash criterion, and mean bias. Results of the six-parameter-based model apparently indicate a similar performance to that of the 13-parameter-based model for the two types of buildings. The model for the six-floor building affords a steadily enhanced performance by increasing the sampling size, while the model for the 13-floor building shows a significantly improved performance with a sampling size of over 200. The results indicate that the heighted structure requires a larger sampling size because it has more degrees of freedom that can influence the model performance. Finally, the proposed models are successfully constructed to estimate the maximum displacement, and applied to obtain fragility curves with various performance levels. Then, the regional seismic damage is assessed in Gyeonjgu city of South Korea as an application of the developed models. The damage assessment with the fragility curve provides the structural response from the seismic activities, which can assist in minimizing damage.

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Section: Six-floor Building Analysis For Development Of the Rapid Prediction Modelmentioning

confidence: 99%

Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment

Park

Jung

2021

IJGI

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“…e displacement of the pier-top (u), the curvature of the pier-bottom (κb), and pier-top (κt) and the strain in the longitudinal steel bar (ε) of the piers were selected. In order to make the coverage of IMs as wide as possible, twenty-four IMs were selected based on a closely related research [5,10]. e selected IMs are listed in Table 3.…”

Section: Preliminary Selection Of Ims and Edpsmentioning

confidence: 99%

“…e effect of IMs on structural seismic performance has attracted increasing attention of researchers around the world in the last few decades [7][8][9][10]. Several indicators for evaluating the applicability and adequacy of IMs have been proposed [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A Seismic Demand Model for Bridges Based on IM and EDP Parameter Matching and Bidirectional Optimization

Shuai

Song

2021

Shock and Vibration

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The accuracy of seismic demand models in seismic vulnerability analysis of structures or components mainly depends on the seismic intensity measures (IMs) and engineering demand parameters (EDPs). This paper proposes a novel method to obtain the optimal seismic demand model for the seismic vulnerability analysis of bridges. The method obtains the IM-EDP combination by matching all IMs and EDPs within a wide range one by one, considering the contribution of multiple IM parameters to the seismic response of the structure and avoiding the blindness of EDP selection. The IM is determined by calculating Pearson correlation coefficient and partial correlation coefficient, controlling the correlation between EDP and IM (or IMs) to a minimum to reduce the multicollinearity within the vector IMs and avoid ill-conditioned models. The optimal seismic demand model is obtained by inspecting the scatter plot and residual plot of suboptimal seismic demand models determined from all combinations by guaranteeing efficiency and sufficiency. The efficiency of seismic demand models is guaranteed by controlling the root mean square error (RMSE) and the coefficient of determination (R2). The sufficiency of models is guaranteed by controlling the slope of fitted line. A continuous rigid frame bridge with double thin-walled piers is used as a case study and a dynamic time-history analysis is performed to obtain the seismic vulnerability of bridge with the proposed method. The results show that the proposed method is feasible and ideally suited for optimizing seismic demand model.

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Seismic fragility analysis of clay-pile-pier systems considering the optimization of ground motion intensity measures

Zhang,

Zhang

2023

Earthq. Eng. Eng. Vib.

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Canonical Correlation Analysis of Selecting Optimal Ground Motion Intensity Measures for Bridges

Cited by 8 publications

References 46 publications

Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment

Gaussian Process Regression-Based Structural Response Model and Its Application to Regional Damage Assessment

A Seismic Demand Model for Bridges Based on IM and EDP Parameter Matching and Bidirectional Optimization

Seismic fragility analysis of clay-pile-pier systems considering the optimization of ground motion intensity measures

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