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Öğe Comparison of deep LSTM and machine learning models for predicting compressive strength of fly ash/slag-based geopolymer concrete(Nature Portfolio, 2025) Kina, Ceren; Tanyildizi, Harun; Al Bakri Abdullah, Mohd Mustafa; Razak, Rafiza Abdul; Imjai, ThanongsakIn the production of geopolymer concrete (GPC), using ground granulated blast furnace slag (GGBFS) and fly ash (FA) can reduce the carbon dioxide footprint and decrease the amount of waste materials released into the environment. Finding the compressive strength (fc) of GPC through experiments is time-consuming and costly; thus, applying artificial intelligence models can expedite this process. This study aims to compare the performance of deep Long Short-Term Memory (LSTM) and the machine learning (ML)-based algorithms in predicting the fc of FA/GGBFS-based GPC. Artificial neural networks (ANN), Bootstrap aggregating (Bagging), Least-Squares Boosting (LSBoost) and K-Nearest-Neighbours (kNN) were used for ML-based algorithms. For this goal, data were collected from the previous studies in the literature. The selected input characteristic variables included the chemical composition and quantities of FA and GGBFS, fine and coarse aggregates, sodium hydroxide molarity, alkaline activators, superplasticizer dosage, and curing temperature. Based on sensitivity analysis, the most influential parameter in the fc of FA/GGBFS-based GPC was the fine aggregate content. Performance metrics, error percentage distribution, and Taylor diagrams indicate that the highest accuracy was achieved by LSTM, which had an R-squared value of 0.98. This was followed by ANN, LSBoost, Bagging, and kNN. Notably, LSBoost and ANN also demonstrated strong performance, with R-squared values of 0.94 and 0.95, respectively. Also, Bagging showed acceptable ability for fc estimation of FA/GGBFS-based GPC due to having an R-squared value of 0.88, but kNN had very poor performance.Öğe Durability of Engineered Cementitious Composites Incorporating High-Volume Fly Ash and Limestone Powder(Mdpi, 2022) Turk, Kazim; Kina, Ceren; Nehdi, Moncef L.This study investigates the effects of using limestone powder (LSP) and high-volume fly ash (FA) as partial replacement for silica sand (SS) and portland cement (PC), respectively, on the durability properties of sustainable engineered cementitious composites (ECC). The mixture design of ECC included FA/PC ratio of 1.2, 2.2 and 3.2, while LSP was used at 0%, 50% and 100% of SS by mass for each FA/PC ratio. Freeze-thaw and rapid chloride ions penetrability (RCPT) tests were performed to assess the durability properties of ECC, while the compressive and flexural strength tests were carried out to appraise the mechanical properties. Moreover, mercury intrusion porosimetry (MIP) tests were performed to characterize the pore structure of ECC and to associate porosity with the relative dynamic modulus of elasticity, RCPT and mechanical strengths. It was found that using FA/PC ratio of more than 1.2 worsened both the mechanical and durability properties of ECC. Replacement of LSP for SS enhanced both mechanical strengths and durability characteristics of ECC, owing to refined pore size distribution caused by the microfiller effect. It can be further inferred from MIP test results that the total porosity had a vital effect on the resistance to freezing-thawing cycles and chloride ions penetration in sustainable ECC.Öğe Effect of Fiber Type, Shape and Volume Fraction on Mechanical and Flexural Properties of Concrete(2022) BAŞSÜRÜCÜ, Mahmut; FENERLI, CENK; Kina, Ceren; akbaş, şadiye defneAn experimental study was herein presented focusing the effect of different type, shape and volume fraction of fibers on the hardened properties of concrete including compressive, splitting tensile and flexural strengths at 7 and 28 curing days. A control concrete mixture with no fiber was prepared and six fiber reinforced concrete mixtures were designed by using two different types of fibers which were steel fibers with different shapes (short straight and hooked end) and polypropylene fiber with the volume fraction of 0.4% and 0.8%. The load-deflection curves and toughness of the specimens were analyzed based on ASTM C1609. The results showed that the utilization of short straight steel fibers with 0.8% volume fraction was most efficient at improving the compressive strength while the use of 0.8% long hooked end steel fibers provided better splitting tensile and flexural strengths. Besides, the long hooked end steel fibers with the volume fraction of 0.8% contributed to an excellent deflection hardening behavior resulting in higher load deflection capacity and toughness at peak load, L/600 and L/150. On the other hand, with incorporation of polypropylene fiber, all strength values were decreased regardless of the volume fraction and curing days.Öğe Extreme Learning Machine for Estimation of the Engineering Properties of Self-Compacting Mortar with High-Volume Mineral Admixtures(Springer Int Publ Ag, 2024) Turk, Kazim; Kina, Ceren; Tanyildizi, HarunThe utilization of supplementary cementitious materials obtained from industrial by-products or wastes is one of the most effective ways to minimize the costs as well as environmental impact associated with cement production. This work investigated the effects of the replacement of Portland cement (PC) with (25, 30, 35 and 40%) fly ash (FA) and (5, 10, 15, and 20%) silica fume (SF) by weight as binary and ternary blends on the compressive strength (f(c)) and flexural strength (f(ft)) of self-compacting mortars (SCMs) at 28 and 91 curing days. Extreme learning machine (ELM), support vector regression (SVR), artificial neural network (ANN), and decision tree (DT) models were devised to predict these strengths of SCMs containing high-volume mineral admixture (HVMA). The selected input variables were the number of curing days, water-cementitious material (W/CM), PC, FA, SF, and sand contents, while the f(c) and f(ft) were the output variables. ANOVA results show that the curing time was the most effective parameter for determining both strengths. The results also indicated that ELM achieved superior performance for the prediction of f(c) and f(ft) of SCMs with HVMA compared to SVR, ANN, and DT due to having the highest coefficient of determination values of 0.9802 for both strengths.Öğe Fire resistance of hybrid fiber reinforced SCC: Effect of use of polyvinyl-alcohol or polypropylene with single and binary steel fiber(Techno-Press, 2023) Turk, Kazim; Kina, Ceren; Balalan, EsmaThis study presents the experimental results performed to evaluate the effects of Polyvinyl-alcohol (PVA) and Polypropylene (PP) fibers on the fresh and residual mechanical properties of the hybrid fiber reinforced SCC before and after the exposure of 250 & DEG;C, 500 & DEG;C and 750 & DEG;C temperatures. The compressive and splitting tensile strength, modulus of rupture (MOR), ultrasonic pulse velocity (UPV) as well as toughness and weight loss were investigated at different temperatures. PVA and PP fibers were added into SCC mixtures having only macro steel fiber and also having binary hybridization of both macro and micro steel fiber. The results showed that the use of micro steel fiber replaced by macro steel fiber improved the fresh and hardened properties compared to the use of only macro steel fiber. Moreover, it was emphasized that PVA or PP enhanced the residual flexural performance of SCC, generally, while it negatively influenced the workability, weight loss, UPV and the residual strengths with regards to the use of single steel fiber and binary steel fiber hybridization. Compared to the effect of synthetic fibers, PP had slightly more positive effect in the view of workability while PVA enhanced the residual mechanical properties more.Öğe Forecasting the compressive strength of GGBFS-based geopolymer concrete via ensemble predictive models(Elsevier Sci Ltd, 2023) Kina, Ceren; Tanyildizi, Harun; Turk, KazimThe compressive strength (fc) of the concrete is an important parameter in the structural design. However, the assessment of fc via an experimental program is time-consuming, costly, and needs a labor force. Therefore, the forecasting of fc through different algorithms can accelerate and facilitate this process and also provide guidance for scheduling the progress of the construction. While some studies have explored the use of models for the prediction of fc of concrete, the ensemble models that can predict the fc of GPC with industrial by-products is still lacking. Within this scope, decision tree (DT), Bootstrap aggregating (Bagging), and Least-squares boosting (LSBoost) models were devised to predict fc of ground granulated blast furnace slag (GGBFS)-based geopolymer concrete (GPC). The data points collected to devise a GEP model in the previous study were used and the prediction results of the GEP model were compared with the proposed ensemble models in the current study. The age of the specimen, NaOH solution concentration, natural zeolite (NZ) content, silica fume (SF) content, and GGBFS content were used as input parameters, and fc was used as output parameter. According to ANOVA analysis, the age of the specimen was found as the most influential parameter in the determination of the fc of GGBFS-based GPC. Also, Multiple linear regression equation was proposed to estimate the fc of GGBFS-based GPC with the accuracy of 93%. The most accurate model was introduced through performance metrics and the Taylor diagram. The results proved that the highest accuracy and stable predictions were achieved by the LSBoost model with R-squared value of 98.25% followed by GEP model developed in the previous study, DT and Bagging models. However, it is worth mentioning that due to having a high coefficient of correlation values (>%80), DT and Bagging models also have an acceptable ability for predicting fc of GGBS-based GPC.Öğe Geotechnical and Structural Investigations in Malatya Province after Kahramanmaraş Earthquake on February 6, 2023(2023) YILDIZ, Ozgur; Kina, CerenTwo earthquakes with moment magnitudes of 7.7 and 7.6 occured on February 6, 2023, at 04:17 a.m. (with local time, GMT+3) in Kahramanmaraş-Ekinözü Pazarcık and at 13:24 p.m. (with local time, GMT+3) in Kahramanmaraş-Elbistan, respectively, in Turkey. The earthquake was felt in a wide area within Turkey and caused structural destructions and heavy damage of buildings, especially in eleven cities including Adana, Adıyaman, Diyarbakır, Gaziantep, Hatay, Kahramanmaraş, Kilis, Malatya, Osmaniye, Şanlıurfa and Elazığ. The aim of this study was to present the detailed field investigation in Malatya province which was one of the most affected city in the region. The strong ground motion records have been analyzed and PGA distribution maps were presented. Structural defects in damaged and collapsed buildings were examined, and design and manufacturing defects were examined. The performance of soil structures was examined, and the defects demonstrated were evaluated in the context of the geological environment. The study is essential in terms of evaluating the damage and possible causes of the building stock in Malatya city center and its districts after the earthquake. In this sense, a holistic evaluation has been carried out, which can be a useful resource for Anatolian cities with typical building characteristics.Öğe Hybrid portland cement-slag-based geopolymer mortar: Strength, microstructural and environmental assessment(Elsevier, 2025) Kina, Ceren; Tanyildizi, Harun; Acik, VolkanThe aim of the current work is to investigate the strength, microstructure, environmental and economic effects of hybrid ordinary portland cement (PC) and ground granulated blast-furnace slag (GGBS) based geopolymer mortar as an alternative to ordinary cement mortar. Eleven mixtures were prepared for this. In this regard, PC was blended with GGBS content of 0-90 wt% in these mixtures. The designed mortar samples were cured at ambient temperature (20 +/- 2 degrees C) to be more applicable in the construction industry, unlike most geopolymer productions and ordinary PC mortar samples were also produced to be comparable to the designed hybrid PC/ GGBS-based geopolymer mortars. The compressive strength (fc) development, ultrasonic pulse velocity (UPV), and dynamic modulus of elasticity (Edyn) values of these ten-hybrid PC/GGBS-based geopolymer mortars were compared with the designed ordinary PC mortar. The results indicated that the incorporation of 20 % PC with 80 % GGBS in the alkali-activated system had the best 28-day compressive strength value with 74.26 MPa, which was 91.07 % higher than that of the designed ordinary PC mortar. The techniques of scanning electron microscopy (SEM)-EDS, Fourier transform-infrared spectroscopy (FT-IR), and thermogravimetric analysis (TGA) were used to identify the microstructural changes caused by the use of ambient temperature cured hybrid 20 % cement-80 % GGBS based alkali-activated mortar. The relatively higher ratios of Ca/Al and Ca/Si compared to ordinary PC mortar proved the more excellent binding property of the C-A-S-H gel, and a denser microstructure was observed in the SEM results. The superior strength development of the hybrid 20 %cement-80 %GGBS alkaliactivated mortar was confirmed by the formation of highly cross-linked C-S-H and C-A-S-H gels due to the higher degree of polymerization and hydration. Additionally, the designed hybrid 20% cement-80 % GGBS geopolymer mortar presented significant environmental and economic benefits compared to those of ordinary PC mortar, with 32.6 % and 23.5 % lower CO2 emission and cost intensity values, respectively.Öğe Importance of pumice amount in the design of self-compacting lightweight concrete(2024) KARADAĞ, ENES MİRAÇ; Gürocak, Mustafa; Kina, Ceren; Turk, KazimAlthough concrete has high compressive strength values, it has a heavy unit volume and low tensile strength. In this study, the normal-weight aggregate, which takes up the most space in concrete by volume and mass, was partially replaced with pumice aggregate, and macro steel fiber (30 mm) was also added to the mixtures. This experimental work aims to investigate the effect of pumice aggregate amount on the fresh and hardened properties, as well as the flexural performance of the self-compacting lightweight concrete (SCLC). The replacement proportions of pumice aggregate with crushed sand were arranged as 45%, 50%, and 55% of the entire aggregate by weight. Three mixtures, each with 1% macro steel fiber reinforcement and without fiber, were prepared for each mixture scenario. The mix design of these six mixtures was arranged to achieve the self-compacting ability and the workability tests recommended by EFNARC (slump-flow, T50, J-ring) were taken into account. To investigate the mechanical properties (compressive, splitting tensile, and flexural strengths) and flexural toughness of the samples, the specimens were cured in water at 23±2 °C for 28 days. As a result, the unit volume weights of the specimens produced from pumice-substituted mixtures decreased with the increase in the pumice dosage, while the compressive, splitting tensile, and flexural strengths decreased. However, it has been determined that all SCLC mixtures including pumice aggregate provided workability properties in general and had enough compressive strength to be used in the production of structural bearing elements, regardless of fiber content. As a result, the optimum pumice aggregate replacement percentage with crushed sand was found to be 45% and the best flexural performance values of the specimens having macro steel fiber were observed in the ones having 45% pumice aggregate substitution.Öğe Machine Learning Prediction of Residual Mechanical Strength of Hybrid-Fiber-Reinforced Self-consolidating Concrete Exposed to Elevated Temperature(Springer, 2023) Turk, Kazim; Kina, Ceren; Tanyildizi, Harun; Balalan, Esma; Nehdi, Moncef L. L.Establishing the engineering properties of cement-based composites at elevated temperature requires costly, laborious, and time-consuming experimental work. Data-driven models can provide a robust and efficient alternative. In this study, extreme learning machine (ELM), support vector machine (SVM), artificial neural network (ANN), and decision tree (DT) models were trained to predict the residual compressive, splitting tensile, and flexural strengths of hybrid fiber-reinforced self-compacting concrete (HFR-SCC) exposed to high temperatures. Mixtures including macro and micro steel fibers, polyvinyl alcohol (PVA), and polypropylene (PP) were subjected to different temperature levels, leading to an experimental database of 360 specimens. Eleven input parameters including cement, fly ash, water, sand, gravel, fiber type, water reducer, and temperature were deployed. The residual mechanical strengths were targeted as output parameters. ANOVA was used to explore the influence of input parameters. Temperature was found to be the most influential parameter. Dataset consisting of 114 instances was retrieved from pertinent literature and used along with the authors' experimentally generated dataset for residual strength prediction. The experimental results were compared with predictions of ELM, SVM, ANN, and DT. ELM achieved superior performance and can offer a robust tool for predicting the residual mechanical strengths of HFR-SCC upon exposure to high temperature.Öğe Macro-micro-nano and mechanical characteristics of cement clinker-gypsum-slag-based hybrid geopolymer mortars: A novel approach for reducing the cost and carbon footprint(Elsevier, 2025) Tanyildizi, Harun; Kina, Ceren; Acik, VolkanThis study introduced a new binder system that includes gypsum, clinker, and blast furnace slag (BFS) within an alkali-activated system to reduce carbon dioxide (CO2) emissions in cement production. The key innovation lies in separately using clinker and gypsum, eliminating the grinding process and combining them with alkali-activated BFS at varying replacement ratios. In this context, ten ambient temperature-cured (20 +/- 2 degrees C) alkali-activated mortars, blended with clinker, gypsum, and slag, were designed, along with one water-cured control mortar containing only clinker and gypsum. Their flow diameters, as well as the initial and final setting times, were evaluated to assess their fresh properties. The optimal replacement ratio of clinker and gypsum with BFS was determined by assessing the 3-and 28-day compressive strengths, bulk density, and dynamic modulus of elasticity. The results showed that the alkali-activated mortars having 20 wt % clinker + gypsum combined with 80 wt% BFS exhibited the highest 28-day strength of 69.26 MPa. The microstructural characteristics of these samples were identified through scanning electron microscopy/energy dispersive X-ray (SEM/EDX), Fourier Transform Infrared (FT-IR), and Thermogravimetric (TG) analysis. The molar ratios of Ca/Si and Na/Al in alkali-activated BFS mortar blended with 20 wt% clinker + gypsum indicated the predominance of calcium aluminosilicate hydrate (C-A-S-H) and a denser microstructure with an 11 % pore fraction. Nano-indentation tests revealed that the calcium/sodium aluminosilicate hydrate ((C, N)-A-S-H) volume fraction was 35 %. In contrast, no phases related to geopolymerization were observed in the alkali-activated clinker + gypsum mortar, which showed noticeable deep cracks and a 15 % pore fraction. The high-density calcium silicate hydrate (C-S-H) volume was 45 % for pure clinker + gypsum-based mortar and 30 % for the alkali-activated version. Furthermore, replacing 20 wt% clinker + gypsum achieved a CO2 capture of 32.16 % and a cost saving of 20.0 %. Consequently, using clinker + gypsum-without grinding process-into alkali-activated BFS in suitable proportions offered a promising alternative for improving eco-efficiency and sustainability.Öğe Novel hybrid deep-long short-term memory and machine learning algorithms for the crack-healing estimation of eco-friendly engineered cementitious composites(Elsevier, 2026) Kina, Ceren; Tanyildizi, HarunSelf-healing concrete addresses cracks caused by environmental factors and tensile strain, helping to extend its lifespan. While Engineered Cementitious Composite (ECC) is particularly important for self-healing, developing a mix that includes supplementary materials instead of relying solely on cement can help reduce environmental impacts. Therefore, accurately predicting its self-healing capacity is crucial. The goal of this study is to develop two new hybrid models that combine Long Short-Term Memory (LSTM) with Gaussian Process Regression (GPR) and Least-Squares Boosting (LSBoost) models, respectively, as well as their individual algorithms to predict the crack-healing ability of eco-friendly ECC. The fly ash, silica fume, limestone powder dosages, and crack width before self-healing (CW-B) were used as input to predict the crack width of ECC after self-healing (CW-A). The ANOVA analysis revealed that CW-B had the most significant impact on CW-A, accounting for 91.84% of the variation. The individual models-LSTM, GPR, and LSBoost-estimated the CW-B with accuracies of 94.6%, 75.4%, and 64.4%, respectively. However, the performance of GPR and LSBoost improved with their hybrid usage alongside LSTM, achieving accuracies of 95.7% and 90.9%, respectively. The LSTM-GPR hybrid model outperformed all others, as evidenced by its narrow range of point-by-point residuals and Taylor plot. Additionally, the LSTM-LSBoost model, despite being slightly less accurate, still demonstrated acceptable predictive capability. These findings indicate that the novel hybrid LSTM-GPR model is the most effective for the self-healing ability prediction of eco-friendly ECC, achieving higher accuracy and lower error rates compared to actual outcomes.Öğe Predicting sorptivity and freeze-thaw resistance of self-compacting mortar by using deep learning and k-nearest neighbor(Techno-Press, 2022) Turk, Kazi; Kina, Ceren; Tanyildizi, HarunIn this study, deep learning and k-Nearest Neighbor (kNN) models were used to estimate the sorptivity and freeze -thaw resistance of self-compacting mortars (SCMs) having binary and ternary blends of mineral admixtures. Twenty-five environment-friendly SCMs were designed as binary and ternary blends of fly ash (FA) and silica fume (SF) except for control mixture with only Portland cement (PC). The capillary water absorption and freeze-thaw resistance tests were conducted for 91 days. It was found that the use of SF with FA as ternary blends reduced sorptivity coefficient values compared to the use of FA as binary blends while the presence of FA with SF improved freeze-thaw resistance of SCMs with ternary blends. The input variables used the models for the estimation of sorptivity were defined as PC content, SF content, FA content, sand content, HRWRA, water/cementitious materials (W/C) and freeze-thaw cycles. The input variables used the models for the estimation of sorptivity were selected as PC content, SF content, FA content, sand content, HRWRA, W/C and predefined intervals of the sample in water. The deep learning and k-NN models estimated the durability factor of SCM with 94.43% and 92.55% accuracy and the sorptivity of SCM was estimated with 97.87% and 86.14% accuracy, respectively. This study found that deep learning model estimated the sorptivity and durability factor of SCMs having binary and ternary blends of mineral admixtures higher accuracy than k-NN model.Öğe 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, KazimThis 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.Öğe Seismic Performance Assessment of an RC Building Due to 2023 Türkiye Earthquakes: A Case Study in Adıyaman, Türkiye(Mdpi, 2025) Bassurucu, Mahmut; Yildiz, Ozgur; Kina, CerenThe 7.7 and 7.6 magnitude Pazarc & imath;k and Elbistan earthquakes that struck Kahramanmara & scedil; on 6 February 2023 caused widespread structural damage across many provinces and are considered rare in seismological terms. While many reinforced concrete (RC) buildings designed under current earthquake regulations sustained significant damage, some older RC buildings with outdated designs sustained only moderate damage. This study aims to analyze the seismic performance of such older RC buildings to understand why they did not collapse or suffer severe damage. An 8-story RC building in Ad & imath;yaman province, damaged by the earthquake, was considered for analysis. The region's seismicity and local site conditions were assessed through borehole operations, geotechnical laboratory tests, and seismic field tests. The soil profile was modeled, and one-dimensional seismic site response analyses were performed using records from nearby stations (TK 4615 Pazarc & imath;k and TK 4612 G & ouml;ksun stations) to determine the foundation-level earthquake record. Nonlinear static pushover analysis was carried out via SAP2000 and STA4CAD, utilizing site response analysis and test results taken from the reinforcement and concrete samples of the building. The findings, compared with the observed damage, provide insights into the performance of older RC buildings in this region.Öğe Sustainable binary/ternary blended mortars with recycled water treatment sludge using fly ash or blast slag: Characterization and environmental-economical impacts(Springer Heidelberg, 2024) Kina, CerenWater treatment sludge (WTS) is produced daily and disposed of as hazardous material. It would be advisable to use locally available waste products as supplementary cementitious materials that ensure to be disposed of without harming the environment. As a novelty, this research investigated the potential of using recycled WTS with fly ash (FA) and ground-granulated blast furnace slag (BFS) as ternary blended binders. Thus, it can provide an economical solution and alleviate the adverse environmental effects of excessive production of wastes and cement production. Within this scope, the mortars with 0-30 wt% replacement of cement with modified WTS (MWTS) were produced as binary blend, and also, they were combined with FA/BFS as ternary blended binders. Therefore, optimum utilization of waste products into the mortar in terms of rheological, mechanical, durability, microstructural properties, and environmental-economical aspects was examined. Adding 10% recycled WTS as binary caused higher strengths with lower porosity measured by the mercury intrusion porosimeter test and denser microstructure, as revealed by XRD patterns and SEM results. However, the drawbacks of using recycled WTS, in terms of rheological parameters and environmental-economical aspects, were suppressed by adding FA/BFS with comparable strength values. Specifically, cost, CO2 footprint, and embodied energy were reduced by combining 10% MWTS with FA by 8.87%, 37.88%, and 33.07%, respectively, while 90-day compressive and flexural strength were 5.1% and 5.32% lower. This study developed a feasible solution to use recycled MWTS by obtaining more eco-friendly and cost-effective cement-based materials.Öğe Workability, flexural response and shrinkage crack restriction of fiber-reinforced SCC: Effects of low coarse aggregate content and micro fiber type(Elsevier Sci Ltd, 2025) Kina, Ceren; Turk, KazimSelf-compacting concrete (SCC) has become increasingly popular due to its beneficial properties, such as reducing labor and construction time, achieving higher quality finish surfaces, and facilitating the construction of heavily congested structural elements. However, the requirement for a greater volume of paste and fine aggregate in the mix design of SCC, compared to ordinary concrete, raises concerns about increased shrinkage. The novelty of this study lies in the use of a low coarse aggregate-to-total aggregate ratio of 0.25, which aims to diminish the beneficial impact of coarse aggregate content on shrinkage performance. This approach seeks to achieve dimensional stability in SCC by incorporating various types and hybrid forms of fiber and allows to investigate their effects on reducing cracks that arise from restraint. In this sense, four fiber types (doublehooked-end steel fiber as macro, short and long straight steel fiber, and PVA synthetic fiber as micro fibers) and their hybridizations (single, binary, ternary, and quaternary) were utilized.Experimental results showed that among the fiber-reinforced SCC mixtures, although all mixtures met the self-compacting criteria, only the binary blend containing 0.8 %macro steel fiber and 0.2 %short micro steel fiber satisfied both the SF3 and VS2/VF2 class limits, while all were classified in PJ1 according to EFNARC. This binary blended sample also showed the highest compressive strength gain, with increases of 24.45 %, 28.89 %, and 20.72 % compared to the control sample at 3, 28, and 90 curing days, respectively. In terms of flexural strength, the ternary blend of 1 %macro steel fiber, 0.8 %long micro steel fiber and 0.5 %PVA demonstrated the greatest enhancement. It showed a 56.8 % increase relative to the control SCC sample, achieving the highest toughness at 101.7 N-m, and displayed significant multiple-cracking behavior among the 90-day samples. Furthermore, under restrained conditions, the quaternary fiber-blended SCC sample achieved the lowest total crack width and shrinkage strain, measuring 149 mu m and 117 mu epsilon, respectively. In conclusion, in a system with a low ratio of coarse aggregate, these cracks can be effectively controlled by incorporating fibers and adopting a hybrid approach, which not only enhances strength, but also ensures that the fresh properties stay within the SCC standards.
