Journal of Structural and Construction Engineering

Journal of Structural and Construction Engineering

Seismic Performance of Reinforced Concrete and Steel Moment Frames under Successive shocks: Evaluation and Estimation of Deflection Amplification Factor using Artificial Neural Network

Document Type : Original Article

Authors
Elham Rajabi 1
Shaghayegh Pakniat 2
Sanaz Rabet 2
Gholamreza Ghodrati Amiri 3
1 Assistant Professor, Department of Civil Engineering, Tafresh University, 39518-79611, Tafresh, Iran
2 MSc Student, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
3 Professor, Natural Disasters Prevention Research Center, School of Civil Engineering, Iran University of Science & Technology, Tehran, IRAN
10.22065/jsce.2023.408439.3177
Abstract
Structures in seismic active zones are often exposed to earthquakes that occur consecutively in a short time together. Therefore, there is not enough time to repair, rebuild or evacuate the damaged structures under the first shock before the second shocks. Despite what is often assumed by seismic design codes, the designed structures based on a single design earthquake are not capable of predicted service and performance. Considering the high damage potential of successive earthquakes, the seismic performance of RC and steel moment frames under successive shocks has been evaluated by comparing the deflection amplification factor (Cd) in the present paper. In this regard, nonlinear dynamic analysis has been performed for three steel and RC frames with 3, 7, and 11 stories under single and consecutive critical earthquakes. The results indicate that the seismic sequence phenomenon can lead to an increase in Cd for the studied frames. Average Cd for RC and steel frames under single shocks is equal to 3.5 and 3.4 and for consecutive shocks is 3.7 and 4. Also, the largest increase in Cd was about 15% for the 3-story steel frame.In the next step, for more comprehensively investigation of the seismic performance of the studied frames, an ideal artificial neural network is designed and after the sensitivity analysis of the maximum Cd factor, empirical equations are presented to estimate this parameter with acceptable accuracy.
Keywords
Deflection Amplification Factor
Seismic Sequence Phenomenon
Artificial Neural Network
Nonlinear Dynamic Analysis
Empirical Equation

Subjects

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  • Receive Date 31 July 2023
  • Revise Date 06 October 2023
  • Accept Date 17 November 2023