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Öğe Çelik lifli KYB ile üretilen V-şekilli betonarme katlanmış plak elemanların kalınlığı üzerinde farklı lif kombinasyonunun etkisi(İnönü Üniversitesi, 2022) Katlav, MetinKatlanmış plaklar, doğal rijitlikleri ve yüksek yük taşıma kapasitelerinin yanı sıra ekonomik avantajları ve estetik görünümleri nedeniyle bazı yapılarda (endüstriyel yapılar, depo, yüzme havuzları vb.) yaygın olarak kullanılmaktadır. Bu tür betonarme taşıyıcı elemanların uzun açıklıklı yapıların çatı taşıyıcı sisteminde kullanılması yapının hem daha hafif hem de daha ekonomik olmasına sağlayabilir. Bununla birlikte, betonarme katlanmış plakların kalınlığı, eğilme performansı açısından önemli bir parametredir. Kalınlığının eğilme performansı üzerindeki etkisi ile ilgili literatürde herhangi bir deneysel çalışma olmamasına rağmen, katlanmış plakların sayısal analizi üzerine yeterince araştırma bulunmaktadır. Bu çalışmada, çelik lif takviyeli kendiliğinden yerleşen betondan (KYB) üretilmiş V-şekilli betonarme katlanmış plakların kalınlığı üzerinde lif kombinasyonunun etkisi araştırılmıştır. Bu amaçla, kontrol, tek lifli ve karma lifli KYB karışımları, deneme-yanılma yoluyla elde edilmiş olup basınç, yarmada ve eğilmede çekme dayanımı testleri 3, 28 ve 90 günlük numuneler üzerinde belirlenmiştir. Daha sonra, KYB'den üretilen üç farklı plak kalınlığına (60, 70 ve 80 mm) sahip toplam on sekiz adet lifsiz, tek ve karma çelik lif takviyeli V-şekilli betonarme katlanmış plak numunesi hazırlanmıştır. 90 günlük V-şekilli betonarme katlanmış plaklar dört noktalı eğilme yüklemesine maruz bırakılarak, yük taşıma kapasitesi, yük-sehim davranışı, tokluk ve süneklik değerlerinin yanı sıra çatlak dağılımları bulunmuştur. Sonuç olarak, V-şekilli betonarme katlanmış plakların üretiminde özellikle karma çelik lif takviyeli KYB kullanımının plak kalınlığının azaltılması ve eğilme performansının iyileştirilmesi açısından önemli avantajlar sağladığı tespit edilmiştir. Ayrıca, çelik lif takviyeli KYB'den üretilmiş V-şekilli betonarme katlanmış plakların kalınlığının tahmini için regresyon analizi ile elde edilen ampirik bir formül önerilmiş ve bu formülün R2=0.97 ile yüksek doğrulukta bir tahmine sahip olduğu görülmüştür. Bununla beraber ACI 544 esas alınarak bazı varsayımlar ile çelik lif takviyeli KYB'den üretilmiş V-şekilli betonarme katlanmış plakların nominal moment taşıma kapasitesini tahmin etmek için bir tasarım yöntemi de önerilmiştir.Öğe Data-driven moment-carrying capacity prediction of hybrid beams consisting of UHPC-NSC using machine learning-based models(Elsevier Science Inc, 2024) Katlav, Metin; Ergen, FarukThis paper presents, for the first time in the literature, a study on the development of data-driven machine learning (ML) models to predict the moment-carrying capacity of ultra-high performance concrete (UHPC)normal strength concrete (NSC) hybrid beams. A database of 56 specimens of rectangular-section UHPC-NSC hybrid beams subjected to flexural loading is adopted to train the models. In this context, ten ML algorithms that are most preferred in structural engineering applications are selected to develop prediction-based models: linear regression (LR), lasso regression (LASSO), ridge regression (RR), support vector regression (SVR), multilayer perception (MLP), random forest (RF), extremely randomized trees (ERT), extreme gradient boosting (XGBoost), K-nearest neighbors regression (KNN), and adaptive boosting regression (AdaBoost). Moreover, the Shapley additive explanation (SHAP) method is used to assess the impact of the input features on the prediction results. Lastly, user-friendly a graphical user interface (GUI) has been developed to ensure the interpretability of the prediction models and to overcome the black box problem of ML methods. The GUI, which is designed based on the model with the most effective prediction ability obtained from this work, allows design engineers to analyze their own data and customize the parameters of the model for the prediction of the moment-carrying capacity of UHPC-NSC hybrid beams. The results indicated that ML models can be an effective tool for predicting the moment-carrying capacity of UHPC-NSC hybrid beams. In this regard, notably, the XGBoost model exhibited superior performance in terms of prediction accuracy and generalization ability (R2 = 0.996 and 0.945 in the training and test datasets, respectively). On the other hand, according to the SHAP analysis results, the three most important input parameters influencing the moment-carrying capacity of UHPC-NSC hybrid beams are the effective depth (d), UHPC thickness at the bottom of the beam (UHPCbottom layer) and compressive strength of UHPC (fc,UHPC), respectively. Moreover, it has been found that the placement of the UHPC layer at the bottom of the beam rather than at the upper part of the beam is more effective in enhancing the moment-carrying capacity of UHPC-NSC hybrid beams.Öğe Effect of rebar arrangements on the structural behavior of RC folded plates manufactured from hybrid steel fiber-reinforced SCC(Elsevier, 2024) Turk, Kazim; Katlav, Metin; Turgut, PakiIn this paper, for the first time in the literature, the effect of different rebar arrangements on the structural behavior of reinforced concrete (RC) folded plates was investigated. For this purpose, RC folded plate specimens having various rebar arrangements fabricated from high-strength hybrid steel fiber-reinforced self-compacting concrete (HSFR-SCC) were tested by subjecting them to four-point bending loading. Then, the structural behavior properties of RC folded plates, such as crack patterns, failure mode, load-midspan displacement relationship, flexural stiffness, ductility, load-strain behavior, and moment-curvature response, were compared and thoroughly assessed. According to the experimental results, different rebar arrangements except for the detailing of transverse rebar induced the RC folded plates to exhibit a combined plate/beam-slab movement behavior, which resulted in higher load-carrying capacity. Notably, it can be said that the detailing of 90-degree hooked steel was generally more effective on the structural behavior of RC folded plates. In addition, the use of hybrid steel fiber instead of transverse rebar provided resistance against shear stresses at the joints and prevented the plates from separating. This application, in constructing the RC folded plates, can reduce labor costs, increase costeffectiveness, and shorten erection time. Therefore, it is obvious that the use of hybrid steel fiber as an alternative to the detailing of transverse rebar for the construction of RC folded plates will ensure some advantages. In conclusion, it is thought that the findings of the study can provide important guidance on the rebar arrangement of RC folded plates in structural engineering applications for structural engineers and designers.Öğe 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, PakiRecently, 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.Öğe Estimation of the shear strength of UHPC beams via interpretable deep learning models: Comparison of different optimization techniques(Elsevier, 2024) Ergen, Faruk; Katlav, MetinIn this article, optimized deep learning (DL) models with different algorithms are adopted to estimate the shear strength of rectangular ultra-high performance concrete beams (UHPC-Bs) in order to overcome the challenges in traditional mechanics-based approaches. Long short-term memory (LSTM) and gated recurrent unit (GRU) are chosen as the DL models, whereas the recent popular optimization algorithms are phasor particle swarm optimization (PPSO), dwarf mongoose optimization (DMO), mountain gazelle optimizer (MGO), and atom search optimization (ASO). A thorough and reliable dataset of 244 UHPC-Bs test results with ten input features has been used to construct the hybrid DL models. The performance of the optimized hybrid LSTM and GRU models with different algorithms is extensively assessed and compared based on various statistical metrics, error, and score analyses. Then, the model with the best estimation performance is determined and compared with the mechanics-based formulas in the current international design codes. Additionally, Shapley additive explanations (SHAP) analysis is used to assist in the interpretability of DL models and to reveal the effects of input features that contribute to the model's estimation. According to the results of the present work, all DL models successfully estimate the shear strength of UHPC-Bs. Among these models, the MGO-LSTM model stands out compared to the other models in terms of several performance measures for both the training and testing phases, like a higher R-2 value, lower RMSE, MAPE, and MAE values, as well as a smaller error ratio and a higher final score. The performance of the algorithms applied to optimize the hyper-parameters of the LSTM and GRU models can be ranked as follows: MGO > DMO > PPSO > ASO. Moreover, a graphical user interface (GUI) was constructed based on the best estimation model that was built so that the shear strength of UHPC-Bs could be estimated in real-world situations without the need for any extra software or tools. This enables more users to quickly and easily estimate the shear strength of UHPC-Bs, optimize design processes, and decrease experimental testing costs.Öğe Flexural performance of V-shaped RC folded plates: The role of plate thickness and fiber hybridization(Elsevier Sci Ltd, 2023) Katlav, Metin; Turk, Kazim; Turgut, PakiReinforced concrete folded plates (RC-FPs) are frequently used in structures such as industrial buildings, hangars, swimming pools, and sports halls due to their high load-bearing capacity, low self-weight, economic advantages, and architectural appearance. However, experimental studies on the reinforced concrete (RC) behavior of these new-generation structural members are very limited. For this purpose, this article investigated the effect of plate thickness and fiber hybridization on the flexural performance of V-shaped RC-FPs produced from self-compacting concrete (SCC). With this study, the experimental moment-curvature tool was used for the first time to evaluate the flexural performance of V-shaped RC-FP. A total of sixteen large-scale V-shaped RC-FP specimens with different plate thicknesses (50, 60, 70, and 80 mm) and fiber hybridization (single, binary, and ternary) were manufactured and subjected to a four-point loading after a 90-day curing period. After the experimental load-deflection and moment-curvature curves were obtained, load-bearing capacity, toughness, curvature ductility, and effective flexural stiffness values were calculated and also showed in the crack patterns for all large-scale V-shaped RC-FPs. The empirical equations with high-precision have been developed using multiple linear regression analysis for predicting the load-bearing capacity, toughness, curvature ductility, and effective flexural stiffness of V-shaped RC-FPs based on the parameters of plate thickness and fiber hybridization. Consequently, the use of hybrid fiber-reinforced SCC in the production of V-shaped RC-FPs exhibited superior properties in terms of flexural performance and crack behavior, as well as allowing for accelerated erection of the roof carrier system, resulting in significantly reducing construction time and costs. Also, fiber reinforcement rather than an increase in plate thickness induced significant increases in the flexural performance values of the V-shaped RC-FPs, while ternary fiber hybridization was the best.Öğe The impact of different length hooked-end fibers on the structural performance of RC folded plates(Ernst & Sohn, 2024) Katlav, Metin; Turk, Kazim; Turgut, PakiIn this article, the effect of hooked-end fibers with different lengths on the structural performance of RC-FPs fabricated from hybrid fiber-reinforced self-compacting concrete (HFR-SCC) was investigated. For this purpose, a total of 15 full-scale test samples having different plate thicknesses (60, 70, and 80 mm) were produced and tested under bending after a 90-day curing period. Subsequently, load-carrying capacity (P-p), flexural toughness (Fth), and deflection ductility index (mu(u)) of all RC-FPs were found using load-deflection curves obtained from bending tests, while crack patterns were drawn from the samples tested. Besides, high-precision contour plots are proposed to estimate the structural performance values of RC-FPs depending on plate thickness and fiber reinforcing index. As a result, the best structural performance in RC-FPs was obtained from the use of a longer hooked-end steel fiber together with micro steel fiber as a hybrid, followed by the lower length hooked-end steel fibers as singles. Specifically, irrespective of the plate thickness, the hybrid use of longer hooked steel fibers in combination with micro fibers increased the P-p, Fth, and mu(u) values of RC-FPs on average 1.67, 1.76, and 1.57 times, respectively, compared to the control specimens. As for when using the lower length hooked-end fiber as single, the values of P-p, Fth, and mu(u) increased on average 1.57, 1.69, and 1.30 times. Lastly, whereas plate thickness has little effect on improving the structural performance of thin-walled carrier elements such as RC-FPs, adding fibers in different lengths, aspect ratios, and combinations is much more effective. The collective test results demonstrate that using RC-FPs made of HFR-SCC in the roof carrier system of large span structures could improve structural performance, aesthetics, erection time, and earthquake behavior thanks to reduced dead load.Öğe Improved forecasting of the compressive strength of ultra-high-performance concrete (UHPC) via the CatBoost model optimized with different algorithms(Ernst & Sohn, 2024) Katlav, Metin; Ergen, FarukThis paper focuses on the applicability of CatBoost models constructed using various optimization techniques for improved forecasting the compressive strength of ultra-high-performance concrete (UHPC). Phasor particle swarm optimization (PPSO), dwarf mongoose optimization (DMO), and atom search optimization (ASO), which have been very popular recently, are preferred as optimization algorithms. A comprehensive and reliable data set is used to develop the CatBoost models, which include 785 test results with 15 input features. The performance of the CatBoost models (PPSO-CatBoost, DMO-CatBoost, and ASO-CatBoost) optimized with different algorithms is thoroughly assessed by means of various statistical metrics and error analysis to determine the model with the best forecasting capability, and this model is compared with the models obtained from previous studies. In addition, Shapley additive exPlanations (SHAP) analysis is used to ensure the interpretability of the forecasting models and to overcome the black box problem of machine learning (ML) models. The obtained results demonstrate that all CatBoost models outstandingly forecast the compressive strength of UHPC. Among these models, the DMO-CatBoost model stands out compared to the other models in various performance metrics, such as high coefficient of determination (R2) values, low root mean squared error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) values, along with a smaller error ratio. In other words, the RMSE, R-2, MAPE, and MAE values of the DMO-CatBoost model for the training set are 3.67, 0.993, 0.019, and 2.35, respectively, whereas those for the test set are 6.15, 0.978, 0.038, and 4.51. Additionally, the performance ranking of the algorithms used to optimize the hyperparameters of the CatBoost model is as follows: DMO > PPSO > ASO. On the other hand, SHAP analysis showed that age, fiber dosage, and cement dosage significantly influence the compressive strength of UHPC. These findings can guide structural engineers in the design and optimization of UHPC, thus assisting them in developing strategies to improve the strength properties of the material. Finally, based on the best forecasting model developed in this work, a graphical user interface has been developed to easily forecast the compressive strength of UHPC in practical applications without additional tools or software.Öğe 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, KazimHybrid 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.Öğe Investigating the applicability of deep learning and machine learning models in predicting the structural performance of V-shaped RC folded plates(Elsevier, 2024) Katlav, Metin; Ergen, Faruk; Turk, Kazim; Turgut, PakiReinforced concrete folded plates (RC-FPs), which are a special class of shell structures, have recently become very popular in modern architectural and engineering applications because of the need for lightweight and aesthetic structures to cover large areas. However, it is known that studies on the structural performance of RCFPs are insufficient. Therefore, this article presents a study on the development and comparison of different deep learning (DL) and machine learning (ML) models for the prediction of the structural performance of full-scale Vshaped RC-FPs produced from hybrid fiber-reinforced self-consolidating concrete (HFR-SCC) having different plate thicknesses (50, 60, 70, and 80 mm), fiber volumes (1.00% and 1.25%), and combinations (single, binary, and ternary). While vanilla long short-term memory (VLSTM) and bidirectional long short-term memory (BILSTM) are used as DL models, random forest (RF), extremely randomized trees (ERT), and adaptive boosting (AdaBoost) are preferred for ML models. To construct the models, the structural performance results of a total of 44 full-scale V-shaped RC-FPs subjected to four-point bending loading were adopted as the database. In addition to all these, the AdaBoost model is used to determine the relative feature importance of the input parameters. Based on the results, among the DL models, the BILSTM has the best ability to predict the structural performance values of V-shaped RC-FPs (such as R-squared values for maximum load-bearing capacity, cracking load, toughness, and deflection ductility are 0.934, 0.987, 0.972, and 0.812, respectively), while in ML models, this is valid for the ERT (such as R-square values are 0.917 for maximum load-bearing capacity, 0.936 for cracking load, 0.947 for toughness and 0.825 for deflection ductility). On the other hand, DL models predicted all other structural performance values better than ML models, except for deflection ductility. Besides, the most relative important input features for maximum load-bearing capacity and toughness values is plate thickness, whereas for cracking load and deflection ductility values compressive strength is important. In conclusion, it can be emphasized that the use of DL models can provide significant advantages in engineering applications, such as predicting the structural performance of V-shaped RC-FPs.Öğe Investigation of optimized machine learning models with PSO for forecasting the shear capacity of steel fiber-reinforced SCC beams with/out stirrups(Elsevier, 2024) Ergen, Faruk; Katlav, MetinThis article presents a comprehensive investigation of the applicability of optimized machine learning (ML) models with particle swarm optimization (PSO) for forecasting the shear strength of steel fiber-reinforced self-compacting concrete (SFR-SCC) beams with/without stirrups in engineering applications. Firstly, a database containing the results of 101 specimens with nine input features is adopted to train the models. As ML models such as random forest (RF), adaptive boosting regression (AdaBoost), extreme gradient boosting (XGBoost), support vector regression (SVR), and K-nearest neighbors regression (KNN) are considered, whereas the hyper-parameters of these models are set as default by the sklearn module. On the other hand, PSO-ML models (PSO-RF, PSO-AdaBoost, PSO-XGBoost, PSO-SVR, and PSO-KNN) are constructed using particle swarm optimization to find the optimal combination of the hyper-parameters of these default ML models. Afterwards, the forecasting ability of each model is extensively assessed using various performance metrics, error analysis, and score analysis, and the model with the best forecasting ability is determined and compared with existing empirical models. Moreover, Shapley additive explanation (SHAP) analysis is also utilized to ensure the interpretability of the forecasting models and to overcome the black box problem of ML methods. Lastly, based on the best forecasting model developed in this study, a graphical user interface (GUI) has been developed to easily forecast the shear strength of SFR-SCC beams in practical applications. The results of the study clearly illustrate that PSO-ML models exhibit better forecasting capabilities than default models. It can be emphasized from here that the PSO algorithm can be an effective tool to improve the performance of ML models. It should also be pointed out that the use of PSO in simpler algorithms instead of tree-based models can further improve forecasting efficiency. On the other hand, the PSO-RF model has the best performance, with a lower error value and a high final score. And this makes it a more reliable option for predicting the shear strength of the SFRSCC beams compared to empirical equations. In addition, according to the results of SHAP feature importance analysis, the most important input parameters affecting the shear strength of SFR-SCC beams are stirrup rebar ratio (rho v), stirrup yield strength (fyv) and longitudinal rebar ratio (rho t). This information can assist engineers in paying special attention to these features in their design and assessment processes.Öğe KARMA ÇELİK LİFLİ KENDİLİĞİNDEN YERLEŞEN BETONUN ELEKTRİKSEL DİRENCİ(2022) Türk, Kazım; Çiçek, Nazlı; Katlav, Metin; Turğut, PakiBeton yüksek basınç dayanımı yanı sıra çok düşük elektriksel iletkenliği sahiptir. Bu çalışmada kendiliğinden yerleşen betonun (KYB) elektriksel özdirenci, iletkenliği ve sıcaklık artışı üzerinde uzun ve kısa çelik liflerin etkisini, lif kombinasyonu (tek ve karma) ve kısa çelik liflerin boyuna (6 ve 13 mm) bağlı olarak belirlemek için dört adet karışım tasarlanmıştır. Bu karışımlar, lifsiz referans, sadece uzun tek lif takviyeli ve uzun lif ile iki farklı boya sahip kısa çelik lif içeren iki adet karma çelik lif takviyeli karışım olmak üzere dört farklı karışım tasarlanmıştır. Tüm çelik lif takviyeli KYB karışımları hacimce toplam %1 lif içermektedir. Karışımların belirlenmesinde EFNARC tarafından önerilen işlenebilirlik testleri (Çökme-yayılma, t500 ve J-halkası yükseklik farkı) dikkate alınmıştır. Karışımlara ait mekanik özellikler (basınç, yarmada çekme ve eğilme dayanımı) ile elektriksel özdirencin belirlenmesi için numuneler üretilmiş ve toplam 90 gün boyunca 23±2 0C’de su içerisinde kür edilmiştir. Sonuçta çelik lif takviyesinin betonun elektriksel özdirencini düşürdüğü ve dolayısıyla iletkenliğini artırdığı tespit edilmiştir. Bunun yanında karma lifli KYB numunelerinin en düşük elektriksel özdirenç ve en yüksek iletkenlik ile sıcaklık artışına sahip olduğu görülürken, narinliği yüksek olan 13 mm boyunda mikro çelik lifin betonun elektriksel özellikleri üzerinde 6 mm boyunda mikro çelik life göre daha olumlu etkiye sahip olduğu bulunmuştur.Öğe Karma Lif Takviyeli KYB Karışımlarının İşlenebilirlik ve Mühendislik Özelliklerinin Araştırılması(2022) Türk, Kazım; Katlav, Metin; Turğut, PakiBu çalışmada, benzer işlenebilirliğe sahip farklı boyut (makro ve mikro) ve narinlikteki çelik lif takviyeli kendiliğinden yerleşen beton (KYB) karışımların mühendislik ve işlenebilirlik özellikleri araştırılmıştır. Bu amaçla, lifsiz, sadece makro lif ve karma lif içeren KYB olmak üzere toplamda üç adet karışım tasarlanmıştır. Lifli KYB karışımları, EFNARC (2002) komitesi tarafından önerilen kriterlere göre mümkün olan benzer işlenebilirlik esas alınarak elde edilmiştir. Bu sebeple, çökme-yayılma, t500 ve J-halkası işlenebilirlik testleri yapılmıştır. Elde edilen lifli KYB karışımlarından 3, 28 ve 90 günlük basınç, yarmada çekme ve eğilmede çekme dayanımlarının belirlenmesi için numuneler hazırlanmış ve standartlara uygun şekilde test edilmiştir.Sonuç olarak, karışıma hem tekli hem de karma lif ilave edilmesi, karışımların işlenebilirlik özelliklerini olumsuz etkilemiştir. Bunun yanında, KYB karışımlarına narinliği 87 olan düz mikro çelik liflerin ilave edilmesinin basınç ve yarmada çekme dayanımlarında, narinliği 65 olan kancalı uçlu makro çelik liflerin ilave edilmesinin ise eğilmede çekme dayanımı değerlerinde olumlu bir etkiye sahip olduğu bulunmuştur.Öğe Research into effect of hybrid steel fibers on the V-shaped RC folded plate thickness(Elsevier Science Inc, 2022) Katlav, Metin; Turk, Kazim; Turgut, PakiFolded plates have been widely used in some structures, such as industrial buildings, hangar, storage, swimming pools etc., due to their natural stiffness and higher load bearing capacity as well as their economic advantage and aesthetic appearance. The thickness of the reinforced concrete (RC) folded plate is an important parameter in terms of its economic cost and load bearing capacity. The works performed on numerical solution of RC folded plates are enough in the literature although there is no any work related to its thickness effect on flexural behavior. In this work, the behavior of V-shaped RC folded plates having various thicknesses (60, 70 and 80 mm) produced from the self-compacting concrete (SCC) with/out steel fiber are experimentally investigated and developed the empirical formula. After 90-day curing period, full-scale V-shaped RC folded plates are subjected to four-point bending load. The load bearing capacity, load-displacement behavior, toughness and ductility values as well as cracking patterns of all V-shaped RC folded plate specimens are found. It is also seen from experimental results that the use of hybrid fiber reinforced SCC in production of V-shaped RC folded plates provides superior flexural behavior. It is addressed that the thickness of the V-shaped RC folded plates can be effectively reduced and its flexural performance is improved by using hybrid steel fibers. Also, a design method for the V-shaped RC folded plates with hybrid steel fibers is also proposed for estimating the nominal moment bearing capacity of V-shaped RC folded plates with some assumptions based on the ACI 544 procedure.
