scholarly journals Compressive strength of concrete with recycled aggregate; a machine learning-based evaluation

2022 ◽  
Vol 3 ◽  
pp. 100044
Author(s):  
Hamed Dabiri ◽  
Mahdi Kioumarsi ◽  
Ali Kheyroddin ◽  
Amirreza Kandiri ◽  
Farid Sartipi
2021 ◽  
Vol 11 (2) ◽  
pp. 485
Author(s):  
Amirreza Kandiri ◽  
Farid Sartipi ◽  
Mahdi Kioumarsi

Using recycled aggregate in concrete is one of the best ways to reduce construction pollution and prevent the exploitation of natural resources to provide the needed aggregate. However, recycled aggregates affect the mechanical properties of concrete, but the existing information on the subject is less than what the industry needs. Compressive strength, on the other hand, is the most important mechanical property of concrete. Therefore, having predictive models to provide the required information can be helpful to convince the industry to increase the use of recycled aggregate in concrete. In this research, three different optimization algorithms including genetic algorithm (GA), salp swarm algorithm (SSA), and grasshopper optimization algorithm (GOA) are employed to be hybridized with artificial neural network (ANN) separately to predict the compressive strength of concrete containing recycled aggregate, and a M5P tree model is used to test the efficiency of the ANNs. The results of this study show the superior efficiency of the modified ANN with SSA when compared to other models. However, the statistical indicators of the hybrid ANNs with SSA, GA, and GOA are so close to each other.


2021 ◽  
Vol 11 (2) ◽  
pp. 127-136
Author(s):  
Sadaf Noshin ◽  
M. Adil Khan ◽  
M. Salman ◽  
M. Shahzad Aslam ◽  
Haseeb Ahmad ◽  
...  

Abstract In construction industry, demolished construction waste is recently used as reprocessed aggregate to produce environmentally friendly concrete which is a good substitute to normal crush due to increased demand of ecological growth and conservation benefits. Though, the properties of recycled aggregate concrete are smallest as compared to concrete produced from natural aggregate and these properties can be enhanced by adding some materials having cementitious properties. Rice husk ash (RHA) is used as partial replacement of cement in recycled aggregate concrete to improve the properties as well as to conserve the natural resources. The elementary purpose of this investigation is to determine the compressive strength of concrete by the replacement of cement with different percentages of rice husk ash such as 0%, 7.5%, 10%, 12.5%, 15%, and 17.5% respectively with different curing conditions. For the experimental program approximate 198 cylinders (18 for rapid curing, 90 for normal water curing and 90 for acid curing) are casted with the mix proportion of 1:2:4 and water to cement ratio of 0.50 whereas curing is done at the ages of 3,7,14,21 and 28 days. Various experiments are performed on fresh and hardened concrete to determine the effects of rice husk ash on recycled aggregate concrete with different curing conditions. Linear regression analysis is carried out to determine the compressive strength of concrete. It is pragmatic from the slump test results that the workability of recycled aggregate concrete is decreased by increasing the quantity of rice husk ash. This reduction in slump is due to high water absorption of recycled aggregates and rice husk ash. Further, the compressive strength of recycled aggregate concrete with normal and acid curing is decreased by increasing the percentages of rice husk ash. It is also observed that at 28- days of normal water curing for mix M1,M2,M3,M4,M5 and M6 the compressive strength is increased by 0.96%, 2.74% 1.45%,4.50%,4.23% and 4.22% respectively as compared to the compressive strength values at 28 days of acid water curing. Therefore, it is concluded that recycled aggregate concrete with 10 to 12% of rice husk ash is suitable for properties of concrete. The acid water curing has negative impacts on hardened properties of concrete as it reduced the compressive strength of concrete as compared to normal water curing.


2021 ◽  
pp. 073168442110501
Author(s):  
Yaser Moodi ◽  
Mohammad Ghasemi ◽  
Seyed Roohollah Mousavi

Recently, there has been a tendency to use machine learning (ML)–based methods, such as artificial neural networks (ANNs), for more accurate estimates. This paper investigates the effectiveness of three different machine learning methods including radial basis function neural network (RBNN), multi-layer perceptron (MLP), and support vector regression (SVR), for predicting the ultimate strength of square and rectangular columns confined by various FRP sheets. So far, in the previous study, several experiments have been conducted on concrete columns confined by fiber reinforced polymer (FRP) sheets with the results suggesting that the use of FRP sheets enhances the compressive strength of concrete columns effectively. Also, a wide range of experimental data (including 463 specimens) has been collected in this study for square and rectangular columns, confined by various FRP sheets. The comparison of ML-derived results with the experimental findings, which were in a very good agreement, demonstrated the ability of ML to estimate the compressive strength of concrete confined by FRP; the correlation coefficient (R2) for MLP, RBFNN, and SVR methods was equal to 0.97, 0.97, and 0.90, respectively. Similar accuracy was obtained by MLP and RBFNN, and they provided better estimates for determining the compressive strength of concrete confined by FRP. Also, the results showed that the difference between statistical indicators for training and testing specimens in the RBFNN method was greater than the MLP method, and this difference indicated the poor performance of RBFNN.


2013 ◽  
Vol 662 ◽  
pp. 352-355 ◽  
Author(s):  
Qi Jin Li ◽  
Guo Zhong Li

The construction waste was processed into recycled aggregate and was used to substitute for natural aggregate to produce concrete small hollow block with grade of MU7.5. The effect of grain composition, replacement ratios and chemical activator of recycled aggregate on compressive strength of concrete small hollow block was studied. The results shows that through optimized grain composition of recycled aggregate and mixed with appropriate chemical activator, the compressive strength of concrete small hollow block with 100% recycled aggregate can be satisfied with the requirement of MU7.5 concrete small hollow block.


2019 ◽  
Vol 5 (12) ◽  
pp. 7-11
Author(s):  
Rajiv Sonwane ◽  
Pushpendra Kumar Kushwaha ◽  
Jiji M Thomas

Marble Industry produces large amount of waste during mining and processing stages. This waste is dumped on to open land which creates a lot of environmental problems We get recycle aggregate from the old dumped structures and buildings. The main objective of this study was utilization of marble, granite and recycled aggregate waste with polypropylene fiber as a replacement for conventional natural coarse aggregates in concrete. Experimental investigations were carried out to examine the feasibility of use of marble, granite and recycled aggregates waste as coarse aggregates in concrete. Conventional natural coarse aggregates was fully replacement by marble in different percentages 0-60% , granite 0-30% and recycle aggregates 0-40% with polypropylene fiber less than 1% by weight. The concrete formulations were prepared with a constant water.


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