Prediction of Bending Strength of Self-Leveling Glass Fiber Reinforced Concrete

Sadik Alper Yildizel; Mehmet Uzun; Mustafa Tolga Cogurcu

doi:10.18201/ijisae.2019751246

Authors

Sadik Alper Yildizel Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department http://orcid.org/0000-0001-5702-807X
Mehmet Uzun Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department
Mustafa Tolga Cogurcu Konya Technical University, Faculty of Engineering and Natural Sciences, Civil Engineering Department

DOI:

https://doi.org/10.18201/ijisae.2019751246

Keywords:

Bending strength, self-leveling concrete, glass fiber, glass fiber reinforced concrete

Abstract

Many studies have been conducted on the prediction of fiber reinforced concrete strength; however, there are very rare data concerning the prediction of bending strength values of self-leveling glass fiber reinforced concrete. And there is no study for prediction of bending strength of self-leveling glass fiber reinforced concrete from mixture ingredients and slump values. In the present study, relationships between the bending strength and the mixture proportions are explored. An artificial neural network model (ANN) is designed with an extensive experimental data including 395 four-point bending tests, and input parameters as white cement amount, maximum aggregate size, glass fiber content, water cement ratio, superplasticizer and metakaolin content and slump test results. Effect of each parameter on the bending strength is investigated with the developed model. An empirical and user-friendly formula was obtained with the generalization capabilities of the ANN. Results showed that the prediction results are in good agreement with the field data. And these numerical results with high efficiency can make it possible to use the neural design for real-life self-leveling glass fiber reinforced concrete applications.

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Author Biographies

Sadik Alper Yildizel, Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department

Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department

Mehmet Uzun, Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department

Karamanoglu Mehmetbey University, Engineering Faculty, Civil Engineering Department

Mustafa Tolga Cogurcu, Konya Technical University, Faculty of Engineering and Natural Sciences, Civil Engineering Department

Konya Technical University, Faculty of Engineering and Natural Sciences, Civil Engineering Department

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