scholarly journals Behaviour Factor of Ductile Code-Designed Reinforced Concrete Frames

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Massimiliano Ferraioli

The current generation of seismic design codes is based on a linear elastic force-based approach that includes the nonlinear response of the structure implicitly through a response modification factor (named reduction factor R in American codes or behaviour factor q in European codes). However, the use of a prescribed behaviour factor that is constant for a given structural system may fail in providing structures with the same risk level. In this paper, the behaviour factor of reinforced concrete frame structures is estimated by means of nonlinear static (pushover) and nonlinear incremental dynamic analyses. For this purpose, regular reinforced concrete frames of three, five, seven, and nine storeys designed for high ductility class according to the European and Italian seismic codes are investigated, and realistic input ground motions are selected based on the design spectra. Verified analysis tools and refined structural models are used for nonlinear analysis. Overstrength, redundancy, and ductility response modification factors are estimated, and the effects of some parameters influencing the behaviour factor, including the number of bays and the number of storeys, are evaluated. The results are finally compared with those obtained from a previous paper for steel moment-resisting frames with the same geometry. According to the analysis results, the behaviour factors in the case of pushover analysis are significantly higher than those obtained in the case of nonlinear response history analysis. Thus, according to the pushover analysis, the behaviour factor provided by European and Italian standards seems highly conservative. On the contrary, the more refined nonlinear dynamic analysis shows that the code-prescribed value may be slightly nonconservative for middle-high-rise frame structures due to unfavourable premature collapse mechanisms based on column plastic hinging at the first storey. Thus, some modifications are desirable in local ductility criteria and/or structural detailing of high ductility columns to implicitly ensure that the recommended value of the behaviour factor is conservative.

2017 ◽  
Vol 7 (4) ◽  
pp. 428 ◽  
Author(s):  
Ning Ning ◽  
Dehu Yu ◽  
Chunwei Zhang ◽  
Shan Jiang

Author(s):  
Amira Elyamany Mohamed ◽  
Walid A Attia ◽  
Wael M. El-Degwy

Response modification factor is an essential factor in seismic analysis to provide economic design of reinforced concrete structures. Base shear force is divided by the response modification factor to consider the ability of the structure to dissipate energy through plastic hinges. The current study investigates the effects of changing some parameters on response modification factor (R-factor). Four groups of reinforced concrete frames were studied with different number of bays, number of stories, load pattern, and fundamental period of vibration. All reinforced concrete frames were analyzed using SAP 2000 then the straining actions results were used at specific excel sheets which are developed to design reinforced concrete members according to the Egyptian code of practice ECP-203 and ECP-201. Frames were analyzed by nonlinear static analysis (pushover analysis) using SAP2000. A sum of thirty two systems of frames was analyzed. According to the results, every frame has its unique value of R-factor. Accordingly, many parameters should be mentioned and considered at code to simulate the actual value of R-factor for each frame. Response modification factor is affected by many factors like stiffness, fundamental period of vibration, number of bays, frame height, geometry of the structure, etc. The given values of R-factor at ECP-201 can be considered conservative; as the accurate values of R-factor is higher than the given values.


2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Mehdi Nikoo ◽  
Łukasz Sadowski ◽  
Faezehossadat Khademi ◽  
Mohammad Nikoo

The paper presents the use of a self-organizing feature map (SOFM) for determining damage in reinforced concrete frames with shear walls. For this purpose, a concrete frame with a shear wall was subjected to nonlinear dynamic analysis. The SOFM was optimized using the genetic algorithm (GA) in order to determine the number of layers, number of nodes in the hidden layer, transfer function type, and learning algorithm. The obtained model was compared with linear regression (LR) and nonlinear regression (NonLR) models and also the radial basis function (RBF) of a neural network. It was concluded that the SOFM, when optimized with the GA, has more strength, flexibility, and accuracy.


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