Efficiency assessment of ground motion intensity measures in the estimation of dynamic response of reinforced concrete moment frames

Document Type : Original Article

Authors

1 Master of Science in Civil Engineering - Structural Engineering, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran

2 Assistant Professor and Faculty Member, Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran

3 Ph.D. in Civil Engineering - Earthquake Engineering, International Institute of Seismology and Earthquake Engineering, Structural Engineering Research Center, Tehran, Iran

Abstract

Selection of appropriate accelerograms for nonlinear dynamic analysis is one of the most important challenges due to their significant influence on the interpretation of analysis results. A rational method for initial refinement of ground motion records with a minimum computational cost is application of refining process based on an optimum intensity measure (IM) which is able to predict the structural responses in a reliable manner. In this research, a list of intensity measures is considered to determine most effective ones from the point of view of effective relation with the dynamic response of the structure. Selected models in this paper includes four two-dimensional (2D) reinforced concrete (RC) structures of 2, 4, 8, 12 and 20 story with special moment-resisting frame (SMRF) system, which are modeled nonlinearly. Collapse capacity of the structures was obtained using the intensity measure spectral acceleration at the first-mode period of structure Sa(T1) and the Incremental Dynamic Analysis (IDA) under the influence of 40 ground motion records selected from the refined data set to observe the gradual behavior of the structure from the linear stage to collapse. Finally, by establishing a statistical relationship between the dynamic response parameters and 27 intensity measures with the use of Pearson correlation index, the most effective intensity measure that All have an integral form and independent from the period of structure, for each of the selected structures was introduced. By examining the results, it can be said that for the 4 story low-rise structure, the Response Spectrum [Housner] intensity measure and for the 8 and 12 story mid-rise structures, the Housner intensity measure and finally, for the 20 story high-rise structure, the Displacement Response Spectrum intensity measure has the highest correlation among the intensity measures studied.

Keywords

Main Subjects


[1] Wyllie, L. A. and Filson, J. R. (1989). Special supplement Armenia earthquake reconnaissance report. Earthquake
Spectra, Pages 1-175.
[2] Ambraseys, N. N., Melville, C. P., & Adams, R. D. (2005). The seismicity of Egypt, Arabia and the Red Sea: a historical
review. Cambridge University Press, Pages 1-173.
[3] Elenas, A. (1997). Interdependency between seismic acceleration parameters and the behaviour of structures. Soil
Dynamics and Earthquake Engineering, Vol. 16, Issue 5, Pages 317-322.
[4] Elenas, A. (2000). Correlation between seismic acceleration parameters and overall structural damage indices of
buildings. Soil Dynamics and Earthquake Engineering, Vol. 20, Issue 1-4, Pages 93-100.
[5] Elenas, A. Meskouris, k. (2001). Correlation study between seismic acceleration parameters and damage indices of
structures. Engineering Structures, Vol. 23, Issue 6, Pages 698-704.
[6] Liao, W-I. Loh, C.H. Wan, S. (2001). Earthquake responses of RC moment frames subjected to near-fault ground
motions. The Structural Design of Tall and Special Buildings, Vol. 10, Issue 3, Pages 219-229.
[7] Cornell, C. A., & Krawinkler, H. (2000). Progress and challenges in seismic performance assessment. PEER Center
News, Vol. 3, Issue 2, Pages 1-3.
[8] Shome, N., & Cornell, C. A. (1999). Probabilistic seismic demand analysis of nonlinear structures. PEER Report No.
RMS-35, Pacific Earthquake Engineering Research Center. University of California, Berkeley, CA.
[9] Luco, N. (2002). Probabilistic seismic demand analysis, SMRF connection fractures, and near-source effects. Ph.D.
thesis, Dept. of Civil and Environmental Engineering, Stanford University, California.
[10] Kramer, S. L., & Mitchell, R. A. (2006). Ground motion intensity measures for liquefaction hazard evaluation.
Earthquake Spectra, Vol. 22, Issue 2, Pages 413-438.
[11] Molavi, M. Ghafory-Ashtiany, M. Arian-Moghaddam, S. (2015). E fficiency assessment of scalar intensity measures in
predicting engineering demand parameters. In: 7th International Conference on Seismology and Earthquake Engineering.
City: Tehran.
[12] Shome, N. Cornell, C. A. Bazzurro, P. & Carballo, J. E. (1998). Earthquakes, records, and nonlinear responses.
Earthquake Spectra, Vol. 14, Issue 3, Pages 469-500.
[13] Vamvatsikos, D. and Cornell, C. A. (March 2002) Incremental Dynamic Analysis. Earthquake Engineering &
Structural Dynamics, Vol. 31, Issue 3, Pages 491-514.
[14] Haselton, Curt B. and Deierlein, Gregory G. (2007). Assessing Seismic Collapse Safety of Modern
Reinforced Concrete Moment-Frame Buildings. City: Berkeley, Publisher: Pacific Earthquake Engineering Research Center
(PEER).
[15] Seismosoft, SeismoStruct. [online] Available at: http://seismosoft.com/seismostruct
[16] Arian-Moghaddam, S. Ghafory-Ashtiany, M. Soghrat, M. (2016). Ground-Motion Prediction Equations based on
refined data for dynamic time-history analysis. Earthquakes and Structures, Vol. 11, No. 5, Pages 779-807.
[17] Pearson correlation coefficient, Available at: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
[18 [یخچالیان و همکاران. "انتخاب سنجه شدت مناسب برای پیشبینی ظرفیت فروریزش سازههای فوالدی کوتاه تا میان مرتبه با سیستم قاب خمشی
ویژه". نشریه مهندسی سازه و ساخت، دوره 4 ،شماره ویژه 1 - شماره پیاپی 11 ،تابستان 1396 ،صفحه 98-109.