Probabilistic evaluation and development of seismic fragility curves of high-rise structures by presenting a suitable method for selecting the most optimum probability distribution for all performance levels

Authors
M. Saadat Asfeh 1
F. Daneshjoo 2
1 MSc Student, Iran, Tehran, Tarbiat Modares University, Civil Engineering dept
2 Professor, Iran, Tehran, Tarbiat Modares University, Civil Engineering dept.
DOI: 10.22034/22.2.16
Abstract
Fragility curves are powerful tools to assess and control of possible damages to the existing structures and estimate the exceedance probability from the seismic behavior of the structures under the influence of different earthquake levels. these curves present the probability of damage as a function of the ground motion characteristics. The main goal of the current study is to examine the existing methods and the presentation of a suitable method for the production of analytical seismic fragility curves and the proposal of appropriate relationships for the exceedance probability from different performance levels. For this purpose, three high-rise building frames with 20, 25, and 30 stories with a slimming ratio greater than π, according to the standard 2800 and the sixth issues and tenth issues of the national building regulations of Iran, were designed. Then, by using Perform 3D program, their analytical model was defined and validated. To evaluate the seismic response demand of frames, incremental nonlinear dynamic analysis (IDA) was performed. For IDA analysis, the 22 recommended records in the FEMAP695 guideline and two earthquakes in Iran were used. Spectral acceleration of the first mode of the structure with damping of 5 Percentage (Sa (T1.5%)) was used to introduce the intensity of the earthquake (IM) and the inter story drift ratio was used to introduce the engineering demand parameter (EDP) Or damage measure (DM). To find the appropriate function of the exceedance probability from limit states and use them in the production of fragility curves, the results of IDA analysis and nineteen different probability functions using the suitable program were used. in order that the used distribution describes the sample data in the best manner, the goodness of fit tests was used. the results obtained from the goodness of fit tests show that The probability distribution rank used by researchers (log normal) versus other probability distribution functions varies in ranking the best fitted probability distribution. and selecting the appropriate probability distribution is effective in the conclusions and determining the probability exceedance of the structure from the desired limit states. Therefore, in order to reduce the uncertainty related to the mathematical model (epistemic uncertainty) in the template of a comprehensive view and according to accuracy and the required seismic target, a suitable method for developing fragility curves for types of steel structural systems with different heights with the name of intelligent seismic fragility curve (ISFC) is introduced and presented. Such that if only one distribution is desired to compare several options, including deciding how to reinforce or comparing the seismic performance of several structures to plot the fragility curve, it is recommended: to use the probability distribution "Generalized Extreme Value", due to having more parameters and the ability to fit better than the distribution "log normal", but for more sensitive structures, such as nuclear power plants and hospitals that are of great importance and require high precision or in order to achieve the most accurate fitted possible to decide on about the vulnerability estimation of any structural system, It is then recommended: to estimate the exceedance probability from performance levels at the structure, before fragility analysis, by probabilistic evaluation and using the goodness of fit tests on suitable probability functions, At First, a best fitted probability distribution should be selected at all performance levels and then the vulnerability of structures is estimated by fragility curves.

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Subjects

[1] God Almighty, The Holy Quran, 14 Centuries ago, Surah Al-Zalzalah, Ayah (1).
[2] Kennedy, R. P. et al. (1980). Probabilistic seismic safety study of an existing nuclear power plant, Nuclear Engineering and Design, 59(2), pp. 315–338.
[3]Tantala, M.W., Deodatis, G.J., (2002). Development of Seismic Fragility Curves for Tall Building. Proceedings of the 15th ASCE Engineering Mechanics Conference, Columbia University. New York.
[4] Arizaga, G.,(2006). Earthquake Induced Damage Estimation for Steel Buildings in Puerto Rico.
[5] Güneyisi, E.M., & Altay, G. (2008). Seismic fragility assessment of effectiveness of viscous dampers in R/C buildings under scenario earthquakes, Journal of Structural Safety, 30(5), 461-480.
[6] Sumit.A.Patel et al. (2016). Fragility Analysis of High-Rise Building, Journal of Emerging Technologies and Innovative Research (JETIR), 3(7), pp. 127–133.
[7] Hamidi, H., Pakdaman, J., Jahani, E., Rajabnejad, H. (2018). The Assessment and Comparison of Tall Buildings with Outrigger and Belt Truss Systems Using Fragility Curves, Journal of Structural and Construction Engineering, 5(1), pp. 174-188 (in persian).
[8] Pourzeynali, S., Mobinipour, S. A. (2019). Assessment of the probability of sidesway collapse of tall steel building with special moment resisting frame CEJ. 18 (5), pp. 189-202
(in persian).
[9] Jahan, N., Heidari, A., Gerami, M. (2020). The
Effect of Sequence Earthquake on Fragility Curve
Dual Systems of Low Rise Steel Moment Frame
with Eccentric Braced Frame, Sharif Journal of Civil Engineering, 35.2(4.1), pp. 119-130
(in persian).
[10] Shome, N. (1999). Probabilistic seismic demand analysis of nonlinear structures.
[11] Jalayer, F. (2003). Direct probabilistic seismic analysis, implementing non-linear dynamic assessments: Stanford University.
[12] Baker, J. W. and Cornell, C. A. (2006). Vector-valued ground motion intensity measures for probabilistic seismic demand analysis, PEER Report 2006/08, Pacific Earthquake Engineering Research Center-College of Engineering, University of California, Berkeley.
[13] Khalfan, M. et al. (2013). Fragility curves for residential buildings in developing countries: A case study on non-engineered URM homes in Bantul, Indonesia, MSc Thesis, Department of Civil Engineering, McMaster University, Hamilton, Ontario, Canada.
[14] CSI ETABS, 2016, v.16.2.1, Integrated Building Design Software.
[15] User Guide Perform-3D, Nonlinear analysis and performance assessment for 3D structures (Version7). California: Computers and Structures, Inc; 2011.
[16] Building and Housing Research Center Iranian Code of Practice for Seismic Resistant Design of Buildings, Standard. 2800. 4th Edition, Tehran, Iran, 2014 (in persian).
[17] Iranian National Building Regulations, Sixth issue, (Load On The Buidings) National Building Regulation Office, Tehran, Iran, 2013 (in Persian).
[18] Iranian National Building Code (INBC), Tenth issue, Design and Construction of Steel Structures: Ministry of Housing and Urban Development, Tehran, Iran .2013 (in persian).
[19] Thai, H. and Kim, S. (2011). Practical advanced analysis software for nonlinear inelastic dynamic analysis of steel structures, Journal of Constructional Steel Research, 67(3), pp. 453–461.
[20] FEMA 356, (2000). Prestandard and Commentary for the Seismic Rehabilitation of Buildings, Federal Emergency Management Agency.
[21] Vamvatsikos, D. and Allin Cornell, C. (2002). Incremental dynamic analysis, Earthquake Engineering and Structural Dynamics, 31(3), pp. 491–514.
[22] FEMA-P695, (2009). Quantification of Building Seismic Performance Factors.
[23]http://peer.berkeley.edu/products/strong ground motion db.html.4
[24] Massey, F. J. (1951). The Kolmogorov-Smirnov Test for Goodness of Fit, J. Am. Stat. Assoc., 46 (253), pp. 68–78.
[25] Stephens, M.A. (1979). The Anderson-Darling statistic. Technical Report No. 39. Stamford University.
[26] Aval, S. B. B. and Verki, A. M. (2014). Systematical Approach to Evaluate Collapse Probability of Steel MRF Buildings Based on Engineering Demand and Intensity Measure, International Conference On Advances in Civil, Structural and Mechanical Engineering (ACSME), Bangkok, Thailand.
Modares Civil Engineering journal
Volume 22, Issue 2
May and June 2022
Pages 289-300