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Experimental Examination of the Behavior of Shotcrete-Reinforced Masonry Walls and Xgboost Neural Network Prediction Model

  • Research Article-Civil Engineering
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Abstract

In this study, the effects of reinforcement using polypropylene fiber dry-mix shotcrete on the behaviors of U-shaped masonry walls were experimentally studied, and predicting modeling was performed with XGBoost. Firstly, five full-scale masonry specimens were constructed. A specimen was left unstrengthened. The other four specimens were coated with dry-mix shotcrete with layer thicknesses of 50 and 100 mm, reinforced with additional amounts of polypropylene fiber. All specimens were tested under reversible and cyclic out-of-plane loads. The results showed that the strengthened specimens had a considerably higher ultimate load-carrying and energy absorption capacities than the bare one. In the second stage of the study, an XGBoost neural network model was developed, predicting the ultimate load capacity and energy absorption capacity with data affecting the result of the model. The ultimate load capacity and energy absorption capacity values obtained as a result of the tests were compared with the results derived from the experiments, and then it was observed that the results of XGBoost modeling were quite close to the results obtained from experimental data. Thus, the thickness of shotcrete required for the desired data can be painlessly predicted using XGBoost model without the need for were experimentally studied.

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Acknowledgements

This study was supported by Scientific and Technological Research Council of Turkey (TUBİTAK) with the Project Number of 111M335.

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Authors and Affiliations

  1. Department of Computer Technologies, Isparta University of Applied Sciences, Isparta, Turkey

    Ahmet Ali Süzen

  2. Department of Civil Engineering, Isparta University of Applied Sciences, Isparta, Turkey

    Melda Alkan Çakıroğlu

  3. Department of Civil Engineering, Mehmet Akif Ersoy University, Burdur, Turkey

    Gülhan İnce

  4. Department of Civil Engineering, Suleyman Demirel University, Isparta, Turkey

    Hamide Tekeli Kabas

Authors
  1. Melda Alkan Çakıroğlu
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  2. Gülhan İnce
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  3. Hamide Tekeli Kabas
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  4. Ahmet Ali Süzen
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Correspondence to Ahmet Ali Süzen.

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The original publication of the article was revised: The order of authors have been corrected.

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Çakıroğlu, M.A., İnce, G., Kabas, H.T. et al. Experimental Examination of the Behavior of Shotcrete-Reinforced Masonry Walls and Xgboost Neural Network Prediction Model. Arab J Sci Eng 46, 10613–10630 (2021). https://doi.org/10.1007/s13369-021-05466-1

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