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    Comparison of extreme learning machine and deep learning model in the estimation of the fresh properties of hybrid fiber-reinforced SCC
    (Springer London Ltd, 2021) Kina, Ceren; Turk, Kazim; Atalay, Esma; Donmez, Izzeddin; Tanyildizi, Harun
    This paper studied the estimation of fresh properties of hybrid fiber-reinforced self-compacting concrete (HR-SCC) mixtures with different types and combinations of fibers by using two different prediction method named as the methodologies of extreme learning machine and long short-term memory (LSTM). For this purpose, 48 mixtures, which were designed as single, binary, ternary and quaternary fiber-reinforced SCC with macro-steel fiber, two micro-steel fibers having different aspect ratio, polypropylene (PP) and polyvinylalcohol (PVA), were used. Slump flow, t(50) and J-ring tests for designed mixtures were conducted to measure the fresh properties of fiber-reinforced SCC mixtures as per EFNARC. The experimental results were analyzed by Anova method. In the devised prediction model, the amounts of cement, fly ash, silica fume, blast furnace slag, limestone powder, aggregate, water, high-range water-reducer admixture (HRWA) and the fiber ratios were selected as inputs, while the slump flow, t(50) and the J-ring were selected as outputs. Based on the Anova analysis' results, the macro-steel fiber was the most important parameter for the results of slump-flow diameter and t(50), while the most important parameter for the results of J-ring was fly ash. Furthermore, it was found that the use of more than 0.20% by volume of 6/0.16 micro-steel fiber positively influenced the fresh properties of SCC mixtures with hybrid fiber. On the other hand, the inclusion of steel fiber instead of synthetic fiber into SCC mixture as micro-fiber was more advantageous in terms of workability of mixtures as result of hydrophobic nature of steel fibers. This study found that extreme learning machine model estimated the slump flow, t(50) and J-ring with 99.71%, 81% and 94.21% accuracy, respectively, while deep learning model found the same experimental results with 99.18%, 77.4% and 84.8% accuracy, respectively. It can be emphasized from this study that the extreme learning machine model had a better prediction ability than the deep learning model.
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    Electrical conductivity and heating performance of hybrid steel fiber-reinforced SCC: The role of high-volume fiber and micro fiber length
    (Elsevier, 2023) Turk, Kazim; Cicek, Nazli; Katlav, Metin; Donmez, Izzeddin; Turgut, Paki
    Recently, it has become very popular to develop electrically conductive concrete composites for active deicing and snow-melting of transportation infrastructure. These composites should have stable electrical conductivity and a uniform heating performance, as well as high mechanical and durability properties, for a sustainable solution. In this context, the main motivation of this study is to develop an electrically conductive hybrid steel fiber reinforced self-compacting concrete (HSFR-SCC) composite for ice and snow removal applications. The electrical conductivity and heating performance of self-compacting concrete (SCC) mixtures having different fiber volumes (1.00, 1.25, and 1.50%) and the combination of macro steel fiber with micro steel fibers having lengths of 13 and 6 mm as single and hybrid were experimentally investigated for the first time. For this purpose, a total of ten SCC mixtures were designed, one of which was non-fiber Control, the others had steel fiber volumes of 1.00, 1.25, and 1.50% and different fiber combinations. Workability (slump-flow, T500 and J-ring) tests on HSFR-SCC mixtures were performed with reference to EFNARC. Then, mechanical (compressive and flexural strengths), electrical resistivity, and heating performance tests of 90-day HSFR-SCC samples were carried out. Before the electrical resistivity and heating performance tests, HSFR-SCC samples were kept in an oven at 105 & PLUSMN; 5 degrees C for 24 h to measure their most critical state (dry) performance. Moreover, using multiple linear regression analysis, empirical equations and contour plots were developed to predict the electrical resistivity and temperature increase values of HSFR-SCC samples depending on fiber volumes and combinations. Considering the experimental results, electrically conductive HSFR-SCC mixtures with satisfactory workability and high strength were obtained. The addition of various volumes and combinations of steel fiber to SCC significantly improved the electrical conductivity and heating performance of the concrete, while the mixtures with hybrid fiber were the best for all fiber volumes. As for the different micro fibers added to the HSFR-SCC mixtures, the 13 mm length micro steel fiber was much more effective in improving the electrical resistivity and heating performance of the samples compared to the 6 mm length micro steel fiber. Also, it was found that the fiber-reinforced index of electrically conductive HSFR-SCC samples could be 0.87 for effective and efficient electrical conductivity.
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    Experimental investigation and explainable artificial intelligence-based modeling of punching shear behavior in self-compacting concrete flat-slabs with low hybrid fiber content
    (Pergamon-Elsevier Science Ltd, 2026) Ari, Abdulkerim; Katlav, Metin; Donmez, Izzeddin; Turk, Kazim
    Flat-slab systems manufactured with self-compacting concrete (SCC) incorporating low hybrid fiber content offer a promising alternative for improving punching shear performance while enhancing constructability in building applications. In this paper, the punching shear behavior of flat-slabs produced with single, binary, and ternary fiber-reinforced SCC was experimentally investigated in terms of load-deflection response, ductility, toughness, cracking behavior, and failure mode. In parallel, a comprehensive database comprising 268 fiber-reinforced concrete flat-slab test results collected from the literature was established, and artificial intelligence (AI)based predictive models were developed to estimate punching shear capacity (Vpun). Model performance was evaluated using statistical indicators, whereas SHapley Additive exPlanations (SHAP) feature importance and partial dependence plots (PDPs) were employed to enhance interpretability and reveal the governing parameters influencing punching capacity. The outcomes demonstrate that binary hybrid fiber systems provide the most effective enhancement in punching capacity and post-cracking performance, even at low fiber contents, outperforming conventional solutions such as shear studs. Among the developed AI models, the Extra Trees Regressor and Random Forest algorithms exhibited the highest prediction accuracy for the Vpun. Finally, the AI models were integrated into a user-friendly graphical interface to facilitate practical engineering applications. Overall, this research contributes by experimentally validating low-fiber SCC flat-slabs as an efficient punching solution and by proposing an explainable, data-driven decision-support framework for engineering design.
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    Improvement of fresh and hardened properties of a sustainable HFRSCC using various powders as multi-blended binders
    (Elsevier Sci Ltd, 2023) Donmez, Izzeddin; Katlav, Metin; Turk, Kazim
    Hybrid fiber-reinforced self-compacting concrete (HFRSCC) has been very popular in recent years due to its high mechanical, durability and flexural performance. HFRSCC properties are also closely related to its workability properties. Therefore, a high proportion of binder material is required to provide a uniform distribution of the fibers in the matrix. The use of mineral admixtures replaced by cement has a vital importance to improve especially the workability of HFRSCC mixtures, resulting in reduction of CO2 emission because the production of 1 ton Portland cement releases about 1 ton of CO2. For this reason, in this study, the effects of multi-blended (binary, ternary and quaternary) binders containing Portland Cement (PC), fly ash (FA), ground granulated blast furnace slag (BS) and limestone powder (LP) on the workability (Slump-flow, T500, J-ring and V-funnel) and hardened (compressive, splitting tensile and flexural tensile strength) properties of HFRSCC as well as flexural performance for 7, 28 and 90 days are investigated. The first of three group mixtures in this study consists of only control mixture (Control) without fiber and mineral admixture blends (MAB), in second group there are four SCC mixtures with only MAB replaced by cement as binary, ternary, quaternary SCC-MAB and the last group also includes four SCC mixtures with both mineral admixtures same as second group and hybrid fiber (HFRSCC-MAB). The total binder amount, water/binder ratio, fine aggregate/all aggregate ratio and fiber hybridization are kept constant while the mineral admixture type and blending system are variable parameters. According to the test results, among the HFRSCC-MAB blends, the quaternary blend system performed the best in terms of workability, followed by the binary blends containing FA. In addition, when it came to ultimate strengths, hybrid fiber -reinforced samples with ternary blends performed best for compressive strength, while hybrid fiber-reinforced samples with binary blends containing FA performed best for splitting tensile and flexural tensile strengths. Finally, it has been seen that the use of various powders as multi-blended binders is a successful solution to obtain high workability for uniform distribution of fibers in HFRSCC as well as high compressive strength and flexural performance, resulting in economical, eco-friendly and sustainable composite.
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    Loading rate effect on shear behavior of stirrupless RC beams with hybrid steel fiber
    (Elsevier Science Inc, 2025) Erol, Yahya; Donmez, Izzeddin; Katlav, Metin; Turgut, Paki; Turk, Kazim
    Even with decades of experimental and analytical investigation, the shear behavior of reinforced concrete (RC) elements remains one of the most complex and least understood phenomena in structural engineering. The inherently brittle and sudden nature of shear failure makes it particularly critical, especially in stirrupless RC beams where multiple interacting parameters govern the response. Among these, the combined effects of loading rate and fiber reinforcement, particularly hybrid fiber systems, have not been adequately explored in existing research. Motivated by this gap, the present study investigates the shear behavior of stirrupless RC beams cast with self-compacting concrete (SCC) incorporating three configurations: non-fiber, single-type macro steel fiber, and hybrid (macro + micro) steel fiber. The beams were tested under two different loading rates (1.60 mm/min and 40 mm/min) and evaluated in terms of load-time behavior, crack patterns and failure mode, load-deflection response, shear capacity and toughness. The results reveal that the combined effect of the loading rate and hybrid steel fiber reinforcement causes a significant transformation in the shear behavior of stirrupless RC beams. That is, at 1.60 mm/min, the addition of fibers led to an average increase of 103 % in ultimate shear capacity compared to non-fiber RC specimens, while this enhancement reached approximately 152 % at 40 mm/min. Notably, hybrid steel fiber-reinforced RC beams exhibited the highest improvement, achieving up to 163 % higher shear capacity under high loading rate. All in all, the findings of this study not only deepen the understanding of loading rate-dependent shear behavior in fiber-reinforced RC beams fabricated from SCC, but more importantly, they provide a practical foundation for future applications in structural engineering. The demonstrated capacity enhancement-particularly with hybrid steel fiber reinforcement under high loading rates-suggests that fiber reinforcement-based design strategies can effectively replace conventional shear reinforcement in certain scenarios. These results support the development of safer, more ductile, and construction-efficient RC systems for use in dynamically loaded structures such as bridges, seismic zone buildings, industrial slabs, and precast elements.
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    Research on bond behavior between steel rebar and self-compacting geopolymer concrete (SCGC) containing recycled aggregate by large-scale beams: The role of different hybrid activator content and precursor materials
    (Elsevier Sci Ltd, 2025) Utu, Rumeysa; Katlav, Metin; Donmez, Izzeddin; Kina, Ceren; Turk, Kazim
    This paper aims to experimentally evaluate, for the first time in the literature, the bond strength between steel rebar and self-compacting geopolymer concrete (SCGC) containing 100 % recycled aggregates, considering the effects of different hybrid activator ratios and precursor material combinations, using large-scale reinforced concrete (RC) beams. With this aim, a total of twelve full-scale SCGC beams, each with dimensions of 200 x 300 x 2000 mm, were produced with different hybrid activator ratios ((Na2SiO3 / (Ca(OH)2 + Na2SiO3)= 0.15, 0.20, 0.25) and precursor material combinations (single, binary and ternary) and tested under four-point bending loading after a 90-day curing period. Test outcomes were compared and evaluated based on main structural performance parameters, including crack patterns and propagation, failure modes, load-midspan displacement curves, load-strain behavior, and bond strength. Moreover, the predictive performance of some existing mechanics-based models for predicting bond strength was evaluated for spliced steel rebar in the SCGC beams. According to the experimental outcomes, both the hybrid activator ratio and the precursor material combinations had remarkable effects on the bond behavior of SCGC beams. In general, lower hybrid activator ratios primarily induced flexural cracks concentrated within the pure bending region, while increasing the hybrid activator content led to a greater number of cracks, particularly transforming into inclined (shear) cracks in the shear region. As for the influence of precursor materials, binary blends-the combination of silica fume (SF) and ground granulated blast furnace slag (BS)-consistently provided superior structural performance, characterized by improved crack control, enhanced load-carrying capacity, and higher bond strength. Notably, the 0.50SF+ 0.50BS_0.15 N specimen with a 0.15 hybrid activator ratio achieved the highest peak load of 96.58 kN and the maximum bond strength of 4.31 MPa among all tested specimens. Furthermore, while existing mechanical bond strength models offered moderately accurate predictions for SCGC, they failed to comprehensively account for the unique interaction mechanisms inherent to geopolymer systems. Therefore, this study underscores the importance of optimizing both activator dosage and precursor synergy to ensure reliable predicted bond performance in SCGC. All in all, these results are expected to provide valuable guidance for structural engineers seeking to implement environmentally friendly, durable, and structurally efficient SCGC members in real-world construction applications.
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    The workability, mechanical, and electrical properties of steel fiber-reinforced SCC incorporating ultra-fine copper slag as fine aggregate
    (Ernst & Sohn, 2025) Katlav, Metin; Donmez, Izzeddin; Kaygusuz, Asim; Turgut, Paki; Turk, Kazim
    Ultra-fine copper slag (CS), a byproduct of the copper industry, is al waste material that is produced in large volumes annually, and its disposal and management are a major environmental concern. Therefore, the utilization of CS in various sectors, especially in the production of construction and building materials, offers enormous potential for both environmental sustainability and economic benefits. In this research, the feasibility of using CS at a ratio of 0%, 25%, 50%, 75%, and 100% by replacing fine aggregate in steel fiber-reinforced self-compacting concrete (SFR-SCC) with high-volume steel fiber (1.50% by volume) has been explored for the first time in the literature. To identify the workability properties of SFR-SCC mixes incorporating 0%, 25%, 50%, 75%, and 100% ultra-fine CS by replacing the fine aggregate, slump-flow, flow times (T500) and J-ring tests were performed, whereas compressive strength (fc), splitting tensile strength (fct), and modulus of elasticity (Ec) tests were applied to the samples for different curing days to evaluate the mechanical properties. Additionally, electrical resistivity/conductivity tests were conducted to determine the electrical properties as well. The experimental results revealed that the inclusion of ultra-fine CS into SFR-SCC mixes with high-volume fiber improved the slump-flow and T500 values, whereas the use of ultra-fine CS above 50% induced a remarkable increase in the T500 value. In addition, the addition of ultra-fine CS caused significant decreases in J-ring height difference (Delta H) values, and a 4-times decrease in Delta H value was observed when the CS ratio was raised from 0% to 100%. In this context, in terms of workability, all mixes exhibited acceptable stability with minimal segregation tendency. On the other hand, the mechanical performance of SFR-SCC samples with different ultra-fine CS ratios was found to be better than those without CS; specifically, the samples incorporating 25% ultra-fine CS reached outstanding values such as fc, fct, and Ec with 83.4, 9.1, and 40.4 GPa, respectively. Furthermore, increasing the CS content in SFR-SCC samples led to considerable improvements in electrical properties, with the CS content raising the electrical conductivity values by an average of 60%. Consequently, it has been proven that the use of ultra-fine CS by replacing fine aggregate in SFR-SCC mixes having high-volume steel fiber improves both the workability and mechanical properties as well as its electrical performance, resulting in high-performance, eco-friendly composites. Thus, it also contributes to the protection of natural resources and the sustainable utilization of industrial waste as well as providing an innovative solution that improves the performance of building materials.