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

Terlumun Sesugh , Michael Onyia , Okafor Fidelis

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.

Keywords

Compression strength prediction, Self-compacting concrete, Artificial intelligence

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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