Amirkabir Journal of Civil Engineering

Amirkabir Journal of Civil Engineering

Analysis of Mathematical Models for Predicting the Mechanical Resistance of Concrete Reinforced with Steel Fibers Using Experimental and Machine Learning Methods

Document Type : Research Article

Authors
Mohmmad Hossein Taghavi Parsa 1
Morteza Esmaeili 2
mohammadreza adlparvar 3
1 University of Qom
2 Iran University of Science and Technology
3 Associate professor civil engineering department technical& engineering faculty university of qom
10.22060/ceej.2026.20086.8164
Abstract
The purpose of this article is to present an optimal mathematical model for predicting the mechanical resistance of concrete reinforced with steel fibers. For this purpose, while studying and investigating the relationships of previous researchers for predicting the compressive, tensile and bending strengths of fiber concrete reinforced with steel fibers, the optimal mathematical relationships governing the problem have been investigated by machine learning method. The focus of the current research is on those concretes reinforced with steel fibers, which are made of smooth, wavy and double-crossed fibers on a macro scale. During this research, the mathematical relationships extracted from the machine learning method, which is used to model the prediction of compressive, tensile and bending strengths of concrete reinforced with steel fibers and by applying the symbolic regression method based on a database consisting of 2283 The provided international data is checked. The efficiency of the models used in this research has been measured using error analysis statistics such as RMSE and MAPE. The results show that the parameters of the size of the largest aggregate, modulus of elasticity, compressive strength of control concrete, water-cement ratio, volume percentage and length of fibers, dimensional ratio of fibers and tensile or bending strength related to the type of output investigated for fiber concrete have the greatest effect. They are resistant to prediction. Examining the results shows that the formulas presented for predicting the strength of reinforced concrete for the examined fibers have considerable accuracy compared to the previous mathematical relationships.
Keywords
Fiber Concrete
Machine Learning
Experimental Formulas
Steel Fibers
Modeling Algorithms
Subjects
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Amirkabir Journal of Civil Engineering
Volume 57, Issue 10
January 2026
Pages 1807-1838