Experimental investigation and prediction of compressive strength of high-strength concrete containing waste ceramic powder using gene expression programming

Document Type : Original Article

Authors

1 PhD Student, Department of Civil engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.

2 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

3 Isfahan University of Technology (IUT)

Abstract

The high volume of carbon dioxide produced in cement plants and the feasibility of reusing waste materials from factories in recent years has become one of the main concerns of research centers and environmental associations. Therefore, the main purpose of this research is to evaluate the feasibility of reusing waste materials with a focus on waste ceramic powder (WCP), as a semi-active aluminosilicate material that can be replaced as a percentage of cement used in concrete. WCP, in addition to activating the potential of using a waste material in concrete, can also reduce cement consumption. Therefore, in this research, cement replacement percentages between 0 and 50% in three water to cement ratios of 0.3, 0.4 and 0.5 in 24 concrete mixtures have been used to perform compressive strength tests. In order to provide a usable computational model, the gene expression programming (GEP) method has been used to predict the compressive strength of the samples. The results of experimental research indicate that in the ratio of water to cement 0.3 at the age of 90 days, the sample containing 20% of WCP has reached a compressive strength of 72.57 MPa. This result is almost equal to the control sample and therefore the use of this percentage is recommended for this ratio of water to cementitious materials. Finally, the results indicate the very good performance of the GEP method by increasing the number of chromosomes and increasing the correlation coefficient between experimental and numerical data up to 98%. Therefore, the GEP method has a significant advantage over other methods by providing an analytical relationship and high accuracy.

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References

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History

  • Receive Date: 14 February 2021
  • Revise Date: 25 April 2021
  • Accept Date: 07 May 2021

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