masonry infilled frames
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2020 ◽  
Vol 32 ◽  
pp. 101683
Author(s):  
Mohammad Yekrangnia ◽  
Panagiotis G. Asteris

Author(s):  
Sonam Dorji ◽  
Hossein Derakhshan ◽  
Tatheer Zahra ◽  
David P. Thambiratnam ◽  
Alireza Mohyeddin

This paper reviews the approach of eleven national codes on the analysis and design of masonry-infilled frames. It is shown that, in general, codes can be divided into two groups. The first group isolates the masonry and frame members by providing gaps to minimize the interaction between them. This method ensures that the complexities involved in analyzing the structure is avoided. However, the width of the gaps recommended is different for each of the codes. The second group takes advantage of the presence of high stiffness and strength masonry infill. In this technique, an equivalent-strut modeling strategy is mostly recommended. It is shown that the strut model suggested in each of the codes is different. An attempt to obtain a generic model for masonry-infilled frame failed largely due to the existence of many behavior-influencing parameters. Finally, it is suggested to have a paradigm shift in the modeling strategy where the masonry-infilled frames are classified into different categories and a model is suggested for each of them.


2020 ◽  
Vol 26 ◽  
pp. 383-392
Author(s):  
F. Di Trapani ◽  
V. Bolis ◽  
F. Basone ◽  
L. Cavaleri ◽  
M. Preti

2019 ◽  
Vol 18 (5) ◽  
pp. 2191-2246 ◽  
Author(s):  
Filip Anić ◽  
Davorin Penava ◽  
Lars Abrahamczyk ◽  
Vasilis Sarhosis

Buildings ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 121 ◽  
Author(s):  
Tanja Kalman Šipoš ◽  
Kristina Strukar

In order to test the reliability of neural networks for the prediction of the behaviour of multi-storey multi-bay infilled frames, neural network processing was done on an experimental database of one-storey one-bay reinforced-concrete (RC) frames with masonry infills. From the obtained results it is demonstrated that they are acceptable for the prediction of base shear (BS) and inter-storey drift ratios (IDR) in characteristic points of the primary curve of infilled frame behaviour under seismic loads. The results obtained on one-storey one-bay infilled frames was extended to multi-bay infilled frames by evaluating and comparing numerical finite element modelling(FEM) modelling and neural network results with suggested approximating equations for the definition of bilinear capacity by defined BS and IDRs. The main goal of this paper is to offer an interpretation of the behaviour of multi-storey multi-bay masonry infilled frames according to a bilinear capacity curve, and to present the infilled frame’s response according to the contributions of frame and infill. The presented methodology is validated by experimental results from multi-storey multi-bay masonry infilled frames.


2018 ◽  
Vol 177 ◽  
pp. 506-518 ◽  
Author(s):  
Gianni Blasi ◽  
Flavia De Luca ◽  
Maria Antonietta Aiello

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