Evaluation of Structural Reliability of Steel Frames: Interstory Drift versus Plastic Hysteretic Energy

Bojórquez, Edén; Terán‐Gilmore, Amador; Ruiz, Sonia E.; Reyes‐Salazar, Alfredo

doi:10.1193/1.3609856

Cited by 41 publications

(25 citation statements)

References 22 publications

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“…It is observed that the spectral shape presents a clear definition throughout the range of periods. This is very important because the spectral shape of the pseudo-acceleration spectrum is an indicator of the ground motion potential of an earthquake Bojórquez and Iervolino 14 ,Bojórquez et al 20 ; moreover, ground motion intensity measures based on spectral shape are very useful to estimate the seismic fragility of buildings in terms of peak and energy demands Bojórquez et al 21 ,Bojórquez et al 22 . The control of seismic energy demands is very important on structures subjected to long duration ground motion records Teran-Gilmore and Jirsa 23 , Bojorquez et al 24 .…”

Section: Training Resultsmentioning

confidence: 99%

Prediction of Inelastic Response Spectra Using Artificial Neural Networks

Bojórquez

Ruiz

Reyes‐Salazar

2012

Mathematical Problems in Engineering

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Several studies have been oriented to develop methodologies for estimating inelastic response of structures; however, the estimation of inelastic seismic response spectra requires complex analyses, in such a way that traditional methods can hardly get an acceptable error. In this paper, an Artificial Neural Network (ANN) model is presented as an alternative to estimate inelastic response spectra for earthquake ground motion records. The moment magnitude (MW), fault mechanism (FM), Joyner-Boore distance (dJB), shear-wave velocity (Vs30), fundamental period of the structure (T1), and the maximum ductility (μu) were selected as inputs of the ANN model. Fifty earthquake ground motions taken from the NGA database and recorded at sites with different types of soils are used during the training phase of the Feedforward Multilayer Perceptron model. The Backpropagation algorithm was selected to train the network. The ANN results present an acceptable concordance with the real seismic response spectra preserving the spectral shape between the actual and the estimated spectra.

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Section: Training Resultsmentioning

confidence: 99%

Prediction of Inelastic Response Spectra Using Artificial Neural Networks

Bojórquez

Ruiz

Reyes‐Salazar

2012

Mathematical Problems in Engineering

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“…where μ lnEDP|S a (T 1 )�s a and σ lnEDP|S a (T 1 )�s a are the geometric mean and standard deviation of the natural logarithm of the EDP, respectively, and Φ(·) is the standard normal cumulative distribution function. It is important to say as Bojórquez et al [38] indicate that the ground motion records used in the present study allow the use of spectral acceleration at first mode of vibration as intensity measure due to its sufficiency with respect to magnitude and distance and because of the similarity of the spectral shape of the records since they have similar values of the spectral parameter N p [39]. evaluate the structural reliability is the computation of the incremental dynamic analysis; thus, the maximum or residual interstory drift at different values of the ground motion intensity measure which in the present study is S a (T 1 ) is calculated.…”

Section: Evaluation Of Structural Reliabilitymentioning

confidence: 99%

Improving the Structural Reliability of Steel Frames Using Posttensioned Connections

Lopez-Barraza

Reyes‐Salazar

Ruiz

et al. 2019

Advances in Civil Engineering

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In this paper, various moment-resisting steel frames (MRSFs) are subjected to 30 narrow-band motions scaled at different ground motion intensity levels in terms of spectral acceleration at first mode of vibration SaT1 in order to perform incremental dynamic analysis for peak and residual interstory drift demands. The results are used to compute the structural reliability of the steel frames by means of hazard curves for peak and residual drifts. It is observed that the structures exceed the threshold residual drift of 0.5%, which is perceptible to human occupants, and it could lead to human discomfort according to recent investigations. For this reason, posttensioned connections (PTCs) are incorporated into the steel frames in order to improve the structural reliability. The results suggest that the annual rate of exceedance of peak and residual interstory drift demands are reduced with the use of PTC. Thus, the structural reliability of the steel frames with PTC is superior to that of the MRSFs. In particular, the residual drift demands tend to be smaller when PTCs are incorporated in the steel structures.

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“…Compared with acceleration, displacement, and other indicators of general seismic responses of the system, the energy component can give an improved reflection of seismic mechanisms and has the potential to address the effect of earthquake duration and cumulative damage of the system directly [13]. From the perspective of energy, the soil has the capacity for energy dissipation [14,15], and energy transfer occurs between the soil and the upper structure during an earthquake [16,17].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Effects of Soil on the Seismic Energy Responses of an Equipment‐Structure System via Substructure Shaking Table Testing

Luo

Jiang

2019

Shock and Vibration

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This study investigated the real-time substructure shaking table testing (RTSSTT) of an equipment-structure-soil (ESS) system and the effects of soil on the seismic energy responses of the equipment-structure (ES) subsystem. First, the branch modal substructure approach was employed to derive the formulas needed for the RTSSTT of the ESS system. Then, individual equations for calculating the energy responses of the equipment and the structure were provided. The ES subsystem was adopted as the experimental substructure, whereas the reduced soil model was treated as the numerical substructure when the RTSSTT was performed on the ESS system. The effectiveness of the proposed testing method was demonstrated by comparing the test results with those of the integrated finite element analysis. The energy responses of the ES subsystem in the case of rigid ground (i.e., the ES system) were compared with those considering the effects of soil (i.e., the ESS system). The input energy responses of the ES subsystem were found to decrease significantly after taking the effects of soil into account. Differences due to the soil effects should be considered in the seismic design for the ES system.

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Evaluation of Structural Reliability of Steel Frames: Interstory Drift versus Plastic Hysteretic Energy

Cited by 41 publications

References 22 publications

Prediction of Inelastic Response Spectra Using Artificial Neural Networks

Prediction of Inelastic Response Spectra Using Artificial Neural Networks

Improving the Structural Reliability of Steel Frames Using Posttensioned Connections

Analysis of the Effects of Soil on the Seismic Energy Responses of an Equipment‐Structure System via Substructure Shaking Table Testing

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