Intensity measures for the seismic response assessment of plain concrete arch bridges

Jahangiri, Vahid; Yazdani, Mahmoud; Marefat, Mohammad Sadegh

doi:10.1007/s10518-018-0334-8

Cited by 32 publications

(10 citation statements)

References 30 publications

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“…A general evaluation of relationships between various engineering demand parameters (EDPs) and cumulative-, spectrum-, and amplitude-based GMIMs including AI and CAV is summarized in Cosenza and Manfredi (2000), Riddell (2007), Kadaş and Yakut (2013), Ye et al (2013), Mollaioli et al (2013), Ebrahimian et al (2015), and Kostinakis et al (2018). In addition, several investigators have found that AI, CAV, or both sometimes in combination with other GMIMs are optimally correlated with EDPs proposed for buildings and bridges (e.g., Padget et al 2008, Fontara et al 2011, Katona 2012, Elenas 2013, Mollaioli et al 2013, Katona and Tóth 2013a, 2013b, Ebrahimian et al 2015, Hancilar and Çakti 2015, Perrault and Guéguen 2015, Tarbali and Bradley 2015, Massumi and Gholami 2016, Kiani and Pezeshk 2017, Muin and Mosalam 2017, Fiore et al 2018, Jahangiri et al 2018, Kiani et al 2018, Liang et al 2018, Mashayekhi et al 2018, Wang et al 2018). Other investigators have developed relationships correlating these GMIMs with amplitude- and spectrum-based GMIMs (e.g., Wang and Du 2012, Bradley 2012, Du and Wang 2013a, Liu et al 2016, Xu et al 2016) and ground motion duration measures (Bradley 2011).…”

Section: Introductionmentioning

confidence: 99%

Ground Motion Models for the Horizontal Components of Arias Intensity (AI) and Cumulative Absolute Velocity (CAV) Using the NGA-West2 Database

Campbell¹,

Bozorgnia

2019

Earthquake Spectra

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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.

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Section: Introductionmentioning

confidence: 99%

Ground Motion Models for the Horizontal Components of Arias Intensity (AI) and Cumulative Absolute Velocity (CAV) Using the NGA-West2 Database

Campbell¹,

Bozorgnia

2019

Earthquake Spectra

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“…In seismic engineering, ground motion IMs are significantly important parameters for fragility analysis and reliable probabilistic seismic demand analysis (Jahangiri, Yazdani, and Marefat 2018). The most common IMs such as PGA and SaT1 are widely utilized for assessment of bridge vulnerabilities (Nielson and DesRoches 2007).…”

Section: Correlation Sensitivity Analysismentioning

confidence: 99%

Effects of Near-fault Pulse-type Ground Motions on High-speed Railway Simply Supported Bridge and Pulse Parameter Analysis

Zhou

Jiang

Xiang

et al. 2022

Preprint

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Based on an innovative high-speed railway simply supported bridge (HSRSSB) model, this paper conducts the investigation of potential influence of near-fault pulse-type ground motions on a 49-span HSRSSB. To obtain target conclusion, 85 original records of near-fault pulse-type ground motions are collected and are imposed on the simulation model as excitation, dynamic responses including girder displacement, rail displacement, pier moment, bearing deformation, and residual displacement are gathered as well. Linear regression analysis reveals the relationship between dynamic response results mentioned above and intensity measures (IMs). Moreover, 6 typical ground motions are chosen from the 85 records as prototype for pulse parameter analysis. Through the artificial ground motions synthesis, the effects of parameters consisted with pulse amplitude, pulse period, and pulse number on HSRSSB are investigated and discussed. It is concluded that responses of HSRSSB are sensitive to acceleration-type IMs and have the strongest linear relationship with spectral IMs at fundamental period of structure. For pulse parameter, the HSRSSB dynamic responses show positive correlation relationship with pulse amplitude, but negative correlation with pulse period.

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“…Structure-independent IMs (seismic characteristics-based) include peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement, and absolute seismic energy (Freddi et al, 2017). Jahangiri et al (2018) regression of seismic response results for railroad plain concrete arch bridges using finite element method found that root mean square acceleration is the best IM based on efficiency, adequacy, scaling robustness and practicality. Wei et al (2021) conducted a seismic vulnerability analysis using PGA as IMs for a three-span HSRB subjected to earthquakes with different incidence angles, and the results showed that the lateral damage of the structure was more sensitive to the effect of ground motion directionality than the longitudinal damage.…”

Section: Introductionmentioning

confidence: 99%

Influence of site conditions on seismic performance of isolated high-speed railroad bridges

Lin

Xiong

et al. 2022

Advances in Structural Engineering

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Earthquakes have occurred frequently in western China (Sichuan, Tibet, etc.) while the complex site conditions in western regions bring great uncertainty to the seismic performance of isolated high-speed railroad bridges (HSRBs). By studying the relationship between structure-dependent and structure-independent seismic intensity measures, soil site conditions are taken into account in the probabilistic seismic demand model (PSDM), which is applied to analyze the failure probability of the isolated HSRB under different site conditions. Based on the design parameters and test results of a typical isolated HSRB in western region, the analysis of the finite element model of the structure was performed. Probabilistic seismic demand models of the isolated HSRB were developed. The seismic fragility curves of the isolated HSRBs were obtained and the failure probabilities under different site conditions were compared and analyzed. The evaluation of the failure probability that the failure probability of the isolated HSRBs in the site area with seismic intensity of 9 is 35.84% and 78.19% under the soil site categories D and E, respectively. Therefore, the seismic spectrum characteristics of the soil site are an important factor affecting the seismic response of isolated HSRB structures. This study provides a more effective modified PSDM for seismic performance assessment of isolated HSRBs under the different site conditions.

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Intensity measures for the seismic response assessment of plain concrete arch bridges

Cited by 32 publications

References 30 publications

Ground Motion Models for the Horizontal Components of Arias Intensity (AI) and Cumulative Absolute Velocity (CAV) Using the NGA-West2 Database

Ground Motion Models for the Horizontal Components of Arias Intensity (AI) and Cumulative Absolute Velocity (CAV) Using the NGA-West2 Database

Effects of Near-fault Pulse-type Ground Motions on High-speed Railway Simply Supported Bridge and Pulse Parameter Analysis

Influence of site conditions on seismic performance of isolated high-speed railroad bridges

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