Review
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Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review

Year 2024, Volume: 8 Issue: 3, 537 - 550, 28.07.2024
https://doi.org/10.31127/tuje.1422225

Abstract

Concrete is one of the most common construction materials used all over the word. In estimating the strength properties of concrete, laboratory works need to be carried out. However, researchers have adopted predictive models in order to minimize the rigorous laboratory works in estimating the compressive strength and other properties of concrete. Self-compacting concrete which is an advanced form of construction is adopted mainly in areas where vibrations may not be possible due to complexity of the form work or reinforcement. This work is targeted at predicting the compressive strength of self-compacting concrete using artificial intelligence techniques. A comparative performance analysis of all techniques is presented. The outcomes demonstrated that training in a Deep Neural Network model with several hidden layers could enhance the performance of the suggested model. The artificial neural network (ANN) model, possesses a high degree of steadiness when compared to experimental results of concrete compressive strength. ANN was observed to be a strong predictive tool, as such is recommended for formulation of many civil engineering properties that requires predictions. Much time and resources are saved with artificial intelligence models as it eliminates the need for experimental test which sometimes delay construction works.

Ethical Statement

THE AUTHORS DECLARE THAT THE WORK IS ORIGINAL AND THERE IS NO CONFLICT OF INTEREST

Supporting Institution

NILL

Project Number

NILL

Thanks

THANKS TO THE DEPARTMENT OF CIVIL ENGINEERING, UNIVERSITY OF NIGERIA NSUKKA FOR THE OPPOTURNITY TO CARRY OUT THIS RESEARCH. OUR APPRECIATION TO THE TURKISH JOURNAL OF ENGINEERING FOR THE OPPORTUNITY TO PUBLISH OUR RESEARCH WORK IN THIS REPUTABLE JOURNAL. THANKS

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Year 2024, Volume: 8 Issue: 3, 537 - 550, 28.07.2024
https://doi.org/10.31127/tuje.1422225

Abstract

Project Number

NILL

References

  • Gaimster, R., & Dixon, N. (2003). Self-compacting concrete. Advanced Concrete Technology, 3, 1-23. https://doi.org/10.1016/B978-075065686-3/50295-0
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  • Lee, S. C. (2003). Prediction of concrete strength using artificial neural networks. Engineering Structures, 25(7), 849-857. https://doi.org/10.1016/S0141-0296(03)00004-X
  • Madandoust, R., & Mousavi, S. Y. (2012). Fresh and hardened properties of self-compacting concrete containing metakaolin. Construction and Building Materials, 35, 752-760. https://doi.org/10.1016/j.conbuildmat.2012.04.109
  • Tufail, R. F., Naeem, M. H., Ahmad, J., Waheed, H., Majdi, A., Farooq, D., ... & Butt, F. (2022). Evaluation of the fresh and mechanical properties of nano-engineered self compacting concrete containing graphite nano/micro platelets. Case Studies in Construction Materials, 17, e01165. https://doi.org/10.1016/j.cscm.2022.e01165
  • Shi, C., Wu, Z., Lv, K., & Wu, L. (2015). A review on mixture design methods for self-compacting concrete. Construction and Building Materials, 84, 387-398. https://doi.org/10.1016/j.conbuildmat.2015.03.079
  • Hamada, H., Alattar, A., Tayeh, B., Yahaya, F., & Thomas, B. (2022). Effect of recycled waste glass on the properties of high-performance concrete: A critical review. Case Studies in Construction Materials, 17, e01149. https://doi.org/10.1016/j.cscm.2022.e01149
  • Efnarc, S. (2002). Guidelines for Self-Compacting Concrete, Rep. from EFNARC. 44, 32.
  • Tejaswini, G. L. S., & Rao, A. V. (2020). A detailed report on various behavioral aspects of self-compacting concrete. Materials Today: Proceedings, 33, 839-844. https://doi.org/10.1016/j.matpr.2020.06.273
  • Danish, P., & Ganesh, G. M. (2021). Self-compacting concrete—optimization of mix design procedure by the modifications of rational method. In 3rd International Conference on Innovative Technologies for Clean and Sustainable Development: ITCSD 2020 3, 369-396. https://doi.org/10.1007/978-3-030-51485-3_25
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There are 81 citations in total.

Details

Primary Language English
Subjects Structural Engineering
Journal Section Articles
Authors

Terlumun Sesugh 0000-0001-7518-7314

Michael Onyia 0000-0002-0956-0077

Okafor Fidelis 0000-0002-3201-6520

Project Number NILL
Early Pub Date July 11, 2024
Publication Date July 28, 2024
Submission Date January 18, 2024
Acceptance Date March 14, 2024
Published in Issue Year 2024 Volume: 8 Issue: 3

Cite

APA Sesugh, T., Onyia, M., & Fidelis, O. (2024). Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review. Turkish Journal of Engineering, 8(3), 537-550. https://doi.org/10.31127/tuje.1422225
AMA Sesugh T, Onyia M, Fidelis O. Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review. TUJE. July 2024;8(3):537-550. doi:10.31127/tuje.1422225
Chicago Sesugh, Terlumun, Michael Onyia, and Okafor Fidelis. “Predicting the Compressive Strength of Self-Compacting Concrete Using Artificial Intelligence Techniques: A Review”. Turkish Journal of Engineering 8, no. 3 (July 2024): 537-50. https://doi.org/10.31127/tuje.1422225.
EndNote Sesugh T, Onyia M, Fidelis O (July 1, 2024) Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review. Turkish Journal of Engineering 8 3 537–550.
IEEE T. Sesugh, M. Onyia, and O. Fidelis, “Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review”, TUJE, vol. 8, no. 3, pp. 537–550, 2024, doi: 10.31127/tuje.1422225.
ISNAD Sesugh, Terlumun et al. “Predicting the Compressive Strength of Self-Compacting Concrete Using Artificial Intelligence Techniques: A Review”. Turkish Journal of Engineering 8/3 (July 2024), 537-550. https://doi.org/10.31127/tuje.1422225.
JAMA Sesugh T, Onyia M, Fidelis O. Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review. TUJE. 2024;8:537–550.
MLA Sesugh, Terlumun et al. “Predicting the Compressive Strength of Self-Compacting Concrete Using Artificial Intelligence Techniques: A Review”. Turkish Journal of Engineering, vol. 8, no. 3, 2024, pp. 537-50, doi:10.31127/tuje.1422225.
Vancouver Sesugh T, Onyia M, Fidelis O. Predicting the compressive strength of self-compacting concrete using artificial intelligence techniques: A review. TUJE. 2024;8(3):537-50.
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