Estimating the Behavior Factor of Regular Moment Resisting RC Frames Using Gene Expression

Document Type : Original Research

Authors
N. Azhdari 1
S. hashemi 2
A. Fazeli 2
1 Civil Engineering Department., Persian Gulf University
2 Assistant Professor., Civil Engineering Department., Persian Gulf University
10.22034/23.1.6
Abstract
Based on the seismic design, energy absorption by plastic deformation is necessary to prevent structures from collapsing during a severe earthquake. Therefore, estimating the behavior of structures to understand their response to earthquakes is particularly important. Seismic loads applied to structures are more significant than forces applied during design. This reduction in design applied loads is accomplished using a behavior factor. It is necessary to employ a behavior factor when evaluating the behavior of structures using linear analysis.

The behavior coefficient depends on ductility coefficient, structural damping coefficient, soil characteristics, earthquake characteristics, over strength coefficient, and design reliability coefficient. While in seismic code, this coefficient is entirely dependent on the type of lateral strength system used. At the same time, the behavior coefficient depends on the structural geometric properties which are investigated in this paper. Since nonlinear analysis is required to determine the effect of earthquake forces during design and nonlinear dynamic analysis is time-consuming, designers typically use nonlinear static analysis. Nonlinear static analysis is one of the nonlinear analysis methods that use the lateral load to represent the earthquake load on the structure statically and increasingly.

Estimating the behavior factor before starting the design process is a vital aid to designers. In this paper, we have examined the behavior factor of the reinforced concrete (RC) frame using gene expression programming. Gene expression programming is highly effective in this instance. Its effectiveness largely determines the success of the method. Gene expression programming is a class of genetic algorithms that utilizes a population of individuals, selects them based on their fit, and introduces genetic changes via one or more genetic operators.

Numerous inputs are required for this purpose, including the number of stories, the span length, the seismicity of the construction site, and the ratio of the compressive strength of concrete to the yield stress of longitudinal reinforcements. Afterward, 168 RC frames were designed via SAP2000 software, and the behavior factor value was obtained using nonlinear static analysis for each frame and subsequently transferred to the GeneXpro Tools software. The sixth and ninth national building regulations, Iran's seismic code, with the American Concrete Institute Code (ACI318-14), were used to analyze and design the structures examined. In the designed frames, the number of stories is 2, 4, 6, 8, 10, 12, and 15, and the ratio of span length to story height is 1, 15, 2, and 2.5, respectively.

The design base accelerations were 0.35, 0.3, and 0.25 in this study, and the longitudinal reinforcements' yield stress was initially set to 340 MPa and then increased to 400 MPa. The obtained results demonstrate that employing the gene expression programming method makes it possible to estimate the reinforced concrete frame's behavior factor with an acceptable degree of accuracy before initiating the design process. Finally, the results show that the variations of the span length and the number of the stories significantly affect behavior factor. Furthermore, as the number of stories increases, the behavior factor decreases initially and then increases. Moreover, the impact of parameters, such as design base acceleration and yield stress of longitudinal reinforcements, is negligible in calculating the behavior coefficient.

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[1]- Sanaee, A., Tigh.Tiznaghsh, A., 2002. seismic evaluation (linear and nonlinear) of concrete shear walls reinforced with steel plates (composite shear walls). MCS thesis, Iran university of Science and Technology. "In Persian"
[2]- Papanikolaou, V.K., Elnashai, A.S. and Pareja, J.F., 2005. Limits of Applicability of Conventional and Advance Pushover Analysis for Seismic Response Assessment. MAE Center CD Release 05-02.
[3]- ATC., 1995: Structural response modification factors, ATC-19 report, Applied technology council, redwood city, California.
[4]- Louzai, A. and Abed, A., 2015. Evaluation of the seismic behavior factor of reinforced concrete frame structures based on comparative analysis between non-linear static pushover and incremental dynamic analyses. Bulletin of Earthquake Engineering, 13(6), pp.1773-1793.
[5]- Asadi kiadehi M, Bengar H, hayanfar J., 2019. Investigating the behavior factor of the intermediate and special RC moment resisting frame with considering the effect of variable axial load and shear. Modares Civil Engineering Journal.; 19 (1), pp:15-25. "In Persian"
[6]- Hashemi, S.S., Sadeghi, K., Vaghefi, M. and Siadat, S.A., 2020. Evaluation of the response modification factor of RC structures constructed with bubble deck system. Scientia Iranica, 27(4), pp:1699-1713.
[7]- Mohsenian, V. and Mortezaei, A., 2018. Evaluation of seismic reliability and multi level response reduction factor (R factor) for eccentric braced frames with vertical links. Earthquakes and Structures, 14(6), pp:537-549.
[8]- Gamit, K. and Amin, J.A., 2021. Drift and Response Reduction Factor of RC Frames Designed with DDBD and FBD Approach. Journal of The Institution of Engineers (India): Series A, 102(1), pp:137-151.
[9]- Shendkar, M.R., Mandal, S. and Kumar, R.P., 2020. Effect of lintel beam on response reduction factor of RC-infilled frames. Current Science, 118(7), pp:1077-1086.
[10]- Alidadi, N., Mahdaviyan, A., 2018, Modeling of sandy soil magnification coefficient by two methods of neural network and gene expression programming. Earth sciences. 27 (107), pp:87-98. "In Persian"
[11]- Fazeli, A., Memari, F., 2018, Determining the pattern of release of petroleum pollutants in groundwater using gene description programming method. The 1nd national conference on environmental geotechnical, Shiraz 3 and 4 September. "In Persian"
[12]- Johari, A. and Golkarfard, H., 2018. Reliability analysis of unsaturated soil sites based on fundamental period throughout Shiraz, Iran. Soil Dynamics and Earthquake Engineering, 115, pp.183-197.
[13]- Mahdinia, S., Eskandari-Naddaf, H. and Shadnia, R., 2019. Effect of cement strength class on the prediction of compressive strength of cement mortar using GEP method. Construction and Building Materials, 198, pp:27-41.
[14]- Razavi, S.A., Siahpolo, N. and Mahdavi Adeli, M., 2020. A New Empirical Correlation for Estimation of EBF Steel Frame Behavior Factor under Near-Fault Earthquakes Using the Genetic Algorithm. Journal of Engineering, 2020(8), pp:1-13.
[15]- Razavi, S.A., Siahpolo, N. and Mahdavi Adeli, M., 2021. Applying Genetic Algorithm to estimate the behavior factor of EBF steel frames under pulse-type near-fault earthquakes, performance level approach. AUT Journal of Civil Engineering, (9)53, pp.19-19
[16]- Divan, M. and Madhkhan, M., 2011. Determination of Behavior Coefficient of Prefabricated Concrete Frame ith Prefabricated Shear Walls. Procedia engineering, 14, pp:3229-3236.
[17]- Taucer, F., Spacone, E. and Filippou, F.C., 1991. A fiber beam-column element for seismic response analysis of reinforced concrete structures (Vol. 91). Berkekey, California: Earthquake Engineering Research Center, College of Engineering, University of California.
[18]- Sheikh, S.A. and Khoury, S.S., 1993. Confined concrete columns with stubs. ACI Structural Journal, 90, pp:414-414.
[19]- Sheikh, S.A., Shah, D.V. and Khoury, S.S., 1994. Confinement of high-strength concrete columns. ACI Structural journal, 91, pp.100-100.
[20]- Bayrak, O. and Sheikh, S.A., 1998. Confinement reinforcement design considerations for ductile HSC columns. Journal of Structural Engineering, 124(9), pp:999-1010.
[21]- Tasnimi, A., Masoumi, A., 2016, determining the behavior factor of of moment resisting RC frames. Center of building and housing research center, Tehran. "In Persian"
[22]- Uang, C.M., 1991. Establishing R (or R w) and C d factors for building seismic provisions. Journal of structural Engineering, 117(1), pp:19-28.
[23]- Mitchell, M., 1998. An introduction to genetic algorithms. MIT press.
[24]- Ferreira, C., 2001. Gene expression programming: a new adaptive algorithm for solving problems, Complex Systems, 13(2), pp: 87-129
[25]- Vecchio, F.J. and Emara, M.B., 1992. Shear deformations in reinforced concrete frames. ACI Structural journal, 89(1), pp:46-56.
[26]- ACI Committee, 2008. Building code requirements for structural concrete (ACI 318-14) and commentary. American Concrete Institute.
Modares Civil Engineering journal
Volume 23, Issue 1
March and April 2023
Pages 91-104