scholarly journals Shear behaviour of recycled aggregate concrete beams with and without shear reinforcement

2017 ◽  
Vol 141 ◽  
pp. 386-401 ◽  
Author(s):  
Ivan S. Ignjatović ◽  
Snežana B. Marinković ◽  
Nikola Tošić
2016 ◽  
Vol 23 (1) ◽  
pp. 76-84 ◽  
Author(s):  
Hyun-Do YUN ◽  
Won-Chang CHOI

As the demand for sustainable construction materials has risen over recent years, researchers have conducted several studies to expand the practical application of recycled construction materials, such as recycled aggregate. The author’s previous research shows the potential application of recycled aggregate over a broad range of structural mem­ber types. This paper continues the earlier work and investigates the shear behaviour of reinforced recycled aggregate concrete beams without shear reinforcement using findings from the author’s previous research. The variables in the test program are replacement rate (0%, 30%, 60%, and 100%) of recycled aggregate and shear span-to-depth ratio (2.0, 2.5, 3.0, 4.0, and 5.0). This work compares the experimental results with results obtained using current code equations found in American Concrete Institute (ACI) 318 (2014) and equations proposed in the literature. This research has found that the current code equations can adequately predict the shear strength of recycled coarse aggregate concrete beams and possibly can be applied for the use of recycled aggregate in structural elements.


2021 ◽  
Author(s):  
Roya Shoghi Haghdoost

A theoretical study is conducted to investigate the shear behaviour of recycled aggregate concrete (RAC) beams with and without shear reinforcements along with the performance evaluation various Code based/other existing equations in predicting shear strength. In addition, three artificial neural network (ANN) models for shear strength prediction of RAC beams with and without shear reinforcements are developed and their performance validated by using 108 beams from available research studies. Most of the Codes and existing methods underestimate the shear capacity of RAC beams with/without shear reinforcement. However, over estimation of shear strength by Codes/existing methods for about 10% RAC beams needs to be addressed when using such Codes/existing methods for shear strength prediction. All three ANN models are found to predict shear strength of RAC beams. Developed ANN models are able to simulate the effect of shear reinforcement on the shear strength of RAC beams.


2021 ◽  
Author(s):  
Roya Shoghi Haghdoost

A theoretical study is conducted to investigate the shear behaviour of recycled aggregate concrete (RAC) beams with and without shear reinforcements along with the performance evaluation various Code based/other existing equations in predicting shear strength. In addition, three artificial neural network (ANN) models for shear strength prediction of RAC beams with and without shear reinforcements are developed and their performance validated by using 108 beams from available research studies. Most of the Codes and existing methods underestimate the shear capacity of RAC beams with/without shear reinforcement. However, over estimation of shear strength by Codes/existing methods for about 10% RAC beams needs to be addressed when using such Codes/existing methods for shear strength prediction. All three ANN models are found to predict shear strength of RAC beams. Developed ANN models are able to simulate the effect of shear reinforcement on the shear strength of RAC beams.


2012 ◽  
Vol 41 ◽  
pp. 490-497 ◽  
Author(s):  
Sandy Schubert ◽  
Cathleen Hoffmann ◽  
Andreas Leemann ◽  
Konrad Moser ◽  
Masoud Motavalli

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