Estimating the Seismic Behavior Factor of Moment Resisting RC frames with Infill 3D Panels using Gene Expression

Document Type : Research Article

Authors

1 M.Sc. Student, Civil Engineering Department, Persian Gulf University, Bushehr, Iran

2 Assistant Professor, Civil Engineering Department, Persian Gulf University, Bushehr, Iran

Abstract

In recent years, sandwich panels have become one of the common infill panels in the moment resisting frame systems. The behavior of these infill panels has always been discussed by researchers. Based on seismic design, for prevention of structures collapse during the severe earthquake, it is necessary to absorption of energy by plastic deformation. In fact, the seismic applied load to structures is greater than applied force to it during design. This reduction of design applied loads is by behavior factor. Behavior coefficient depends on parameters such as ductility coefficient, structural damping coefficient, soil characteristics, earthquake characteristics, over strength coefficient and design reliability coefficient. Therefore, estimating the behavior of structures is always of particular importance in order to understand their response to earthquakes. In the present study, the behavior factor of moment resisting frames with the sandwich infill panel has been investigated. Also, an equation has been established to calculate the behavior factor, based on various effective parameters. In this regard modeling and nonlinear analysis of moment resisting frames models with the sandwich panels were performed in ETABS 2017. Nonlinear analysis is necessary for determining the effect of earthquake force in during design and nonlinear dynamics analysis is time consuming so usually designers use the nonlinear static analysis. Nonlinear static analysis is one of the nonlinear analysis methods that the lateral load represents the earthquake load and is applied statically and increasingly to the structure. Estimating behavior factor prior to the starting of the design process is an important help to designers. For the process of analysis and design of the researched structures, the national building regulations and also ACI 318-14 have been used in loading, analyzing and designing process. In this paper, we have examined behavior factor of the reinforced concrete (RC) frame with sandwich infill panels using gene expression programming. Gene expression programming is very successful in this case. The success of an issue depends largely on how well it works. Gene expression programming is a genetic algorithm that uses the population of individuals and selects them according to fit and introduces genetic changes using one or more genetic operators. In this modeling, some effective parameters in the performance of moment resisting frames with the sandwich infill panels have been considered in various and variable ways. These parameters include: the number of stories (2, 4, 6, 8, 10, 12, and 15), the ratio of span length to story height (1, 1.5, and 2), the design base acceleration (0.35 and 0.3), ratio of concrete compressive strength to the longitudinal reinforcements yield stress (0.08 and 0.075). After calculating the behavior factor using valid methods, a database was created by using the behavior factors obtained from the models. A mathematical equation was conducted by GeneXproTools software to obtain the behavior factor. The main purpose of this research is to establish an equation to obtain the behavior factor of the moment resisting frames system with the sandwich infill panel based on effective parameters. The obtained equation has resulted in a regression coefficient of 93%. After extracting the relevant functional equations, the sensitivity and parametric study of the behavior factor concerning the parameters of the mentioned variable have been studied.  The result shows that the parameters of the number of stories and the ratio of span length to story height, are the most influential on the behavior factor. In this regard, with increasing the number of stories, the coefficient of behavior increases, and with increasing the ratio of span length to story height, the value of behavior factor decreases.

Keywords

References

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History

  • Receive Date: 30 November 2021
  • Revise Date: 19 July 2022
  • Accept Date: 23 November 2022

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