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Cost-effective FRP solutions for enhancing strength and strain of sustainable concrete made with waste tyre rubber
(2026-12-01)
Saingam, Panumas
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Chatveera, Burachat
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Hussain, Qudeer
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Sua-iam, Gritsada
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Chaimahawan, Preeda
This study investigates the compressive behavior and analytical modeling of natural and rubberized concretes confined with cost-effective glass fiber-reinforced polymer (GFRP) jackets. Forty-two cylindrical specimens were tested under axial compression, including natural aggregate concrete (NAC) and rubberized concretes (RuC) prepared with 20% fine aggregate replacement using coarse (2.0 mm) and fine (0.425 mm) waste tire rubber. Both full and strip GFRP wrapping configurations with two, four, and six layers were examined. The results showed that GFRP confinement substantially enhanced both strength and ductility, transforming brittle failure into a gradual, energy-absorbing response. Full wrapping produced up to 63% and 90% strength increases for NAC and rubberized concretes, respectively, with ultimate strain gains exceeding 1300% in the fine-rubber mix. Strip wrapping achieved moderate yet significant improvements while offering material savings. Analytical models were developed for both concrete types to predict confined stress–strain behavior, achieving strong correlations (R2 = 0.84–0.99) between predicted and experimental data. The derived regression-based formulations successfully captured the influence of confinement pressure, rubber content, and wrapping configuration. These findings demonstrate that GFRP provides an economical and sustainable confinement solution for enhancing the performance of rubberized concrete in structural and retrofitting applications.
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Experimental evaluation of sustainable jute–basalt hybrid FRP systems for flexural strengthening of RC beams with variable wrapping and light-weight aggregate replacement
(2026-12-01)
Saingam, Panumas
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Hanif, Muhammad Adnan
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Ahmed, Fahad
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Chatveera, Burachat
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Sua-iam, Gritsada
This research experimentally assesses the flexural strengthening of reinforced concrete (RC) beams through the use of sustainable jute–basalt (JB) hybrid fiber-reinforced polymer (FRP) systems with variable wrapping schemes and lightweight aggregate (LWA) replacement. A total of 18 beams with identical geometry and reinforcement were tested under four-point bending, including controls, basalt FRP (BFRP), jute FRP (JFRP), and hybrid JB FRP systems in bottom-only, U-wrap, and full-wrap configurations. The results indicate that FRP confinement significantly modified failure modes, transitioning from the brittle crushing in controls to rupture- or debonding-controlled mechanisms. BFRP significantly enhanced strength, achieving up to 36.8% greater capacity in full-wrap beams, while JFRP improved ductility but was more prone to premature debonding. Hybrid JB FRP systems demonstrated the most balanced performance, with U-wrap hybrids achieving 39.6% higher load capacity and maintaining significant deformation capacity even in LWA concrete. Load–strain responses confirmed yielding of steel reinforcement in all cases, though maximum strains were reduced after confinement due to premature fiber debonding or rupture at smaller deflections. The use of LWA reduced ductility of control beams, but hybrid U-wrap systems successfully compensated for this limitation, providing the highest load and deflection values among all specimens. These results emphasize the potential of hybrid natural–mineral FRP systems as sustainable alternatives to synthetic composites, providing competitive ductility and reinforcement for structural retrofitting applications in both conventional and lightweight concretes.
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From Experiment to Prediction: Machine Learning Solutions for Concrete Strength Assessment with Steel Clamps
(2026-02-01)
Saingam, Panumas
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Chatveera, Burachat
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Sua-Iam, Gritsada
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Chaimahawan, Preeda
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Suthumma, Chisanuphong
This study examines the confined compressive strength (Fcc) of circular, square, and rectangular column geometries under varying confinement conditions. Results indicate that circular columns have the highest Fcc values, exceeding those of square and rectangular shapes. Increased confinement through clamps significantly enhances compressive strength. Five machine learning models, Linear Regression, Decision Tree, Random Forest, AdaBoost, and Gradient Boosting, were used to predict Fcc based on geometric and confinement parameters. Linear Regression and Decision Tree models achieved moderate predictive performance, with R2 values of 0.84 and 0.83, respectively, and relatively higher error measures (RMSE, MAE, and MAPE), indicating limited ability to capture complex nonlinear relationships in the data. In contrast, ensemble-based methods demonstrated superior performance. The Random Forest model improved the coefficient of determination to 0.90 while substantially reducing all error metrics, reflecting enhanced generalization through bagging. The boosting-based approaches yielded the best results, with AdaBoost achieving the highest R2 value of 0.99 and the lowest RMSE, MAE, and MAPE among all models, followed closely by Gradient Boosting with an R2 of 0.98. These results confirm that ensemble learning techniques, particularly boosting algorithms, yield more accurate and robust predictions than single learners for the problem studied. Data visualization techniques, including Regression Error Characteristic curves (REC) and SHapley Additive exPlanations (SHAP) value analysis, highlighted model performance and feature importance, emphasizing the roles of confinement and geometry in compressive strength. This research demonstrates the potential of machine learning to optimize structural engineering design and suggests further exploration of alternative shapes and confinement strategies to enhance structural integrity.
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Eco-Friendly Structural Solutions: The Synergy of Waste Rubber and Hemp Fibers in Sustainable Concrete Design
(2026-01-01)
Thansirichaisree, Phromphat
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Mohamad, Hisham
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Chaimahawan, Preeda
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Hussain, Qudeer
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Jirasakjamroonsri, Amornthep
The growing emphasis on sustainable construction has encouraged the integration of recycled and renewable materials into structural concrete. This study investigates the axial compressive behavior of rectangular columns incorporating waste-tire rubber as a partial replacement of fine aggregate (5% and 10%) and external confinement using low-cost hemp ropes. A total of twelve specimen configurations, including unconfined and hemp-confined columns with up to three wrapping layers, were tested under monotonic axial compression. The results show that rubber inclusion reduces initial stiffness and peak strength by up to 46%, yet significantly enhances deformability. Hemp-rope confinement effectively compensates for strength loss, increasing compressive strength by up to 53% and ultimate strain by over 500%, with more pronounced effects in rubberized mixes. Normalized strength and strain trends demonstrate a strong dependence on confinement ratio, particularly for highly deformable concrete. To generalize these behaviors, Popovics-based models were calibrated using nonlinear regression, yielding high predictive accuracy (R2 = 0.94–0.98) for key parameters including peak stress, peak strain, post-peak modulus, and elastic modulus. The proposed expressions closely reproduce the experimental stress–strain response and provide practical tools for modeling confined conventional and rubberized concrete.

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