Mechanical and flexural fatigue behaviour of steel fibre reinforced RAP-based concrete: experimental and machine learning investigation

This study examines the mechanical and flexural fatigue behaviour of concrete with reclaimed asphalt pavement (RAP) aggregates with and without steel fibre reinforcement. The use of RAP as partial replacement for natural aggregates represents a sustainable solution for reduction of construction waste and saving of natural resources. Twenty concrete mixes were prepared with RAP replacement levels varying between 0 and 30% and steel fibre contents varying between 0 and 1.25% by volume. The experimental investigation comprised t evaluation of strength characteristics, stress–strain behaviour, and flexural fatigue performance. Results show that increase in RAP content leads to a gradual decrease in the strength of the concrete due to weaker interfacial transition zone formed between the RAP aggregates and the cementitious matrix. However, the addition of steel fibres significantly enhances the tensile and flexural properties; the optimum steel fibre dosage was found to be 1%. At this dosage the compressive toughness was significantly increased, and the split tensile and flexural strengths improved as much as 45% and 48%, respectively. Stress–strain behaviour of RAP-based fibre reinforced concrete under compression is described by a modified Saenz equation based stress–strain model. The results of flexural fatigue tests indicated that fibre reinforcement substantially improves the fatigue life and endurance limit of RAP-based concrete. Machine learning models based on random forest regression and gradient boosting regression were also developed for the prediction of mechanical properties with the highest predictive accuracy of the gradient boosting model (R 2 = 0.96). The integrated experimental and machine learning framework developed in this study provides a preliminary proof-of-concept methodology for evaluation and optimization of sustainable RAP-based fibre reinforced concrete for pavement applications.

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Journal
Scientific Reports
Published
2026-06-18
DOI
https://doi.org/10.1038/s41598-026-58324-1
Primary Topic
Innovative concrete reinforcement materials
Type
article
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Mechanical and flexural fatigue behaviour of steel fibre reinforced RAP-based concrete: experimental and machine learning investigation

Rathish Kumar Pancharathi, Adamu Mulatu Kumara, Yeswanth Paluri, Siva Shanmukha Anjaneya Babu Padavala et al.
Scientific Reports
Innovative concrete reinforcement materials
article

Mechanical and flexural fatigue behaviour of steel fibre reinforced RAP-based concrete: experimental and machine learning investigation

Rathish Kumar Pancharathi, Adamu Mulatu Kumara, Yeswanth Paluri, Siva Shanmukha Anjaneya Babu Padavala, S. R. R. Teja Prathipati, Heeralal Mudavath
article en

Abstract

This study examines the mechanical and flexural fatigue behaviour of concrete with reclaimed asphalt pavement (RAP) aggregates with and without steel fibre reinforcement. The use of RAP as partial replacement for natural aggregates represents a sustainable solution for reduction of construction waste and saving of natural resources. Twenty concrete mixes were prepared with RAP replacement levels varying between 0 and 30% and steel fibre contents varying between 0 and 1.25% by volume. The experimental investigation comprised t evaluation of strength characteristics, stress–strain behaviour, and flexural fatigue performance. Results show that increase in RAP content leads to a gradual decrease in the strength of the concrete due to weaker interfacial transition zone formed between the RAP aggregates and the cementitious matrix. However, the addition of steel fibres significantly enhances the tensile and flexural properties; the optimum steel fibre dosage was found to be 1%. At this dosage the compressive toughness was significantly increased, and the split tensile and flexural strengths improved as much as 45% and 48%, respectively. Stress–strain behaviour of RAP-based fibre reinforced concrete under compression is described by a modified Saenz equation based stress–strain model. The results of flexural fatigue tests indicated that fibre reinforcement substantially improves the fatigue life and endurance limit of RAP-based concrete. Machine learning models based on random forest regression and gradient boosting regression were also developed for the prediction of mechanical properties with the highest predictive accuracy of the gradient boosting model (R 2 = 0.96). The integrated experimental and machine learning framework developed in this study provides a preliminary proof-of-concept methodology for evaluation and optimization of sustainable RAP-based fibre reinforced concrete for pavement applications.

Scientific Reports
Siddhartha Medical College (IN), National Institute of Technology Warangal (IN), Guizhou University (CN), Wollega University (ET), Jain Vishva Bharati University (IN)
Responsible consumption and production, Life in Land
Openalex Percentile: Top 10%
Innovative concrete reinforcement materials
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