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Öğe Cem I, Cem IIIa ve Borlu Çimento Harçları Üzerine Farklı Agresif Koşulların Etkisi(2014) Yaprak, Hasbi; Demir, İlhami; Kaplan, GökhanBu çalışmada deniz suyu ve amonyum nitrat gibi farklı etkilere maruz kalmış çimento harçlarının direnci araştırılmıştır. Borlu, CEM I ve CEM III/A çimentoları kullanılarak çimento harç numuneleri hazırlanmıştır. Çimento harçlarının genleşme değerlerini belirlemek için 25 x 25 x 285 mm boyutunda harç çubukları, basınç dayanımları için 40x40x160 mm boyutunda prizmalar üretilmiştir. Harç numuneleri %5'lik amonyum nitrat çözeltisi, içme ve deniz suyu olmak üzere üç farklı koşulda, 203 ºC sıcaklıkta 2, 7, 14, 28 ve 90 gün süreyle bekletilmiştir. Tüm ortam koşulları ve yaşlarda en düşük genleşme CEM III/A çimentolu harçlarda bulunmuş, hem deniz suyu ve hem de amonyum nitratlı ortamlara karşı CEM III/A çimentolu harçların daha yüksek direnç sağladığı gözlenmiştir.Öğe Estimating the Properties of Ground-Waste-Brick Mortars Using DNN and ANN(Tech Science Press, 2019) Karaci, Abdulkadir; Yaprak, Hasbi; Ozkaraca, Osman; Demir, Ilhami; Simsek, OsmanIn this study, deep-neural-network (DNN)- and artificial-neural-network (ANN)- based models along with regression models have been developed to estimate the pressure, bending and elongation values of ground-brick (GB)-added mortar samples. This study is aimed at utilizing GB as a mineral additive in concrete in the ratios 0.0%, 2.5%, 5.0%, 7.5%, 10.0%, 12.5% and 15.0%. In this study, 756 mortar samples were produced for 84 different series and were cured in tap water (W), 5% sodium sulphate solution (SS5) and 5% ammonium nitrate solution (AN5) for 7 days, 28 days, 90 days and 180 days. The developed DNN models have three inputs and two hidden layers with 20 neurons and one output, whereas the ANN models have three inputs, one output and one hidden layer with 15 neurons. Twenty-five previously obtained experimental sample datasets were used to train these developed models and to generate the regression equation. Fifty-nine non-training-attributed datasets were used to test the models. When these test values were attributed to the trained DNN, ANN and regression models, the brick-dust pressure as well as the bending and elongation values have been observed to be very close to the experimental values. Although only a small fraction (30%) of the experimental data were used for training, both the models performed the estimation process at a level that was in accordance with the opinions of experts. The fact that this success has been achieved using very little training data shows that the models have been appropriately designed. In addition, the DNN models exhibited better performance as compared with that exhibited by the ANN models. The regression model is a model whose performance is worst and unacceptable; further, the prediction error is observed to be considerably high. In conclusion, ANN- and DNN-based models are practical and effective to estimate these values.Öğe Investigation of effect of sepiolite on the properties of autoclaved aerated concrete(Stowarzyszenie Producentow Cementu, 2015) Demir, İlhami; Savaş, Musa; Yaprak, Hasbi; Doğan, Orhan; Özel, GökhanIn the work the effect of sepiolite addition, replacing quartz sand in the autoclaved cellular concrete (ACC), on the properties of this cement composite was examined. It was found that sepiolite content higher than 10% is decreasing compressive strength of ACC and increasing its moisture content, already at addition of 5%. Also dry density is decreasing quickly up to 15% and from 20% to 25% only slowly. However, thermal conductivity is decreasing substantially from 0.105 to 0.088 for 10% sepiolite addition. 10% of sepiolite is the best level of replacement of quartz sand in ACC.Öğe Investigation of the Effect of Seawater and Sulfate on the Properties of Cementitious Composites Containing Silica Fume(Springer, 2022) Simsek, Osman; Aruntas, H. Yilmaz; Demir, Ilhami; Yaprak, Hasbi; Yazicioglu, SalihConcrete consumes over two billion tons of freshwater every year and 75 % of regions of the world will become water shortages in 2050. Because of increasing freshwater scarcity seawater may become reasonable as an alternative mixing and curing water for concrete. In this study, seawater (SW) was utilized for mixing and curing of concrete and investigated the seawater and sulfate on the properties of cementitious composites containing silica fume (SF). Hence, SF was replaced with the cement at ratios corresponding to 0 %, 2.5 %, 5 %, 7.5 %, 10 %, 12.5 %, and 15 % by weight of cement, and SW and tap water (TW) were used as mixing water in the production of cementitious composites. Thus, the effect of SW on the properties of fresh cement pastes and the flexural and compressive strengths of 7-day, 28-day, and 90-day old cementitious composites were examined. Additionally, the lengthening change values of cementitious composites containing SF that were kept in 5 % Na2SO4 solution for 7-day, 28-day, and 90-day were determined. The SF delayed the setting period while increasing the water requirement of the cement paste. It is determined that the SW accelerated the setting period of cement. In the case when 10 % SF in cementitious composites was used, the maximum compressive and flexural strengths were obtained for cementitious composites produced by mixing with SW and SF fume at an age corresponding to 28-day and 90-day. It was observed that the length change of the cementitious composites decreased due to the increase in the SF replacement ratio.Öğe Performance of cement mortars replaced by ground waste brick in different aggressive conditions(Univ Chemistry & Technology, Prague, 2011) Demir, Ilhami; Yaprak, Hasbi; Simsek, OsmanThis article investigates the sulphate resistance of cement mortars when subjected to different exposure conditions. Cement mortars were prepared using ground waste brick (GWB) as a pozzolanic partial replacement for cement at replacement levels of 0%, 2.5%, 5%, 7.5, 10%, 12.5 and 15%. Mortar specimens were stored under three different conditions: continuous curing in lime-saturated tab water (TW), continuous exposure to 5% sodium sulphate solution (SS), and continuous exposure to 5% ammonium nitrate solution (AN), at a temperature of 20 +/- 3 degrees C, for 7, 28, 90, and 180 days. Prisms with dimensions of 25x25x285 mm, to determine the expansions of the mortar samples; and another set of prisms with dimensions of 40x40x160 mm, were prepared to calculate the compressive strength of the samples. It was determined that the GWB replacement ratios between 2.5% and 10% decreased the 180 days expansion values. The highest compressive strength values were found for the samples with 10% replacement ratio in the TW, SS, and AN conditions for 180 days. The microstructure of the mortars were investigated using scanning electron microscopy (SEM) and the Energy dispersive X-ray (EDX).Öğe Polipropilen Lifli Betonların Yüksek Sıcaklık Sonrası Basınç Dayanımlarının Yapay Sinir Ağları ile Tahmini(Kırıkkale Üniversitesi, 2009) Yaprak, Hasbi; Karacı, AbdulkadirBeton yüksek sıcaklık etkisinde kaldığında önemli ölçüde hasara uğrar. Bu durum istenilmeyen yapısal kusurlara neden olabilir. Polipropilen liflerin ilavesi bu hasarın azaltılmasında kullanılan yöntemlerden biridir. Bu çalısmada lif katkısız, 0.9, 1.35 ve 1.8 kg/m3 polipropilen lif katkılı beton numuneler üretilmis, numuneler laboratuar ortamında olgunlastırılmıs, 28. günün sonunda tüm numuneler 20, 400, 600 ve 800 ºC sıcaklık etkisinde bırakılmıstır. Yüksek sıcaklık etkisinde kalan numunelerin basınç dayanımları test edilmistir. Deneysel olarak bulunan test sonuçlarının yapay sinir ağları (YSA) kullanılarak bulunması amaçlanmıstır. YSA yaklasımı ile deneysel olarak elde edilmis veriler karsılastırıldığında değerlerin birbirine en çok % 3.5 en az % 0.0 hata ile yakın olduğu görülmüstür.Öğe Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks(Springer London Ltd, 2013) Yaprak, Hasbi; Karaci, Abdulkadir; Demir, IlhamiThe present study aims at developing an artificial neural network (ANN) to predict the compressive strength of concrete. A data set containing a total of 72 concrete samples was used in the study. The following constituted the concrete mixture parameters: two distinct w/c ratios (0.63 and 0.70), three different types of cements and three different cure conditions. Measurement of compressive strengths was performed at 3, 7, 28 and 90 days. Two different ANN models were developed, one with 4 input and 1 output layers, 9 neurons and 1 hidden layer, and the other with 5, 6 neurons, 2 hidden layers. For the training of the developed models, 60 experimental data sets obtained prior to the process were used. The 12 experimental data not used in the training stage were utilized to test ANN models. The researchers have reached the conclusion that ANN provides a good alternative to the existing compressive strength prediction methods, where different cements, ages and cure conditions were used as input parameters.Öğe The Effect of Different Aggresive Condition on Mortars of Cem I, Cem II and Boron Cement(Gazi Univ, 2014) Yaprak, Hasbi; Demir, Ilhami; Kaplan, GokhanThis study investigates the sea water and ammonium nitrate resistance of cement mortars when subjected to different exposure conditions. Cement mortar samples were prepared using Boron, CEM I and CEM III/A cements. Mortar specimens were stored under three different conditions: continuous curing in lime-saturated tab water, continuous exposure to sea water, and continuous exposure to 5% ammonium nitrate solution (AN), at a temperature of 20 +/- 3 degrees C, for 2, 7, 14, 28 and 90 days. Prisms with dimensions of 25x25x285 mm, to determine the expansions of the mortar samples; and another set of prisms with dimensions of 40x40x160 mm, were prepared to calculate the compressive strength of the samples. For all environmental conditions and ages, the lowest expansion is found for CEM III/A cement mortars. It has been observed that CEM III/A cement mortars have the highest resistance for both sea water and environments with ammonium nitrate.Öğe The effect of sea water on the properties of concrete with silica fume admixture(Stowarzyszenie Producentow Cementu, 2010) Demir, Ylhami; Yaprak, Hasbi; Simsek, OsmanTwo series of concrete samples with silica fume addition were produced from the mixtures with tap water or sea water, as mixing water. It was found that sea water has no harmful influence on the concrete mix properties, but increase the rate of concrete hardening. This caused the increase of concrete strength, which was observed till the end of measurements i.e. till 90 days. However the increase of strength after 90 days was smaller than after 28 days.Öğe Thermal and Compressive Strength Properties of Sepiolite Substituted Autoclaved Aerated Concrete(Gazi Univ, 2014) Savas, Musa; Demir, Ilhami; Guzelkucuk, Selahattin; Sengul, Cagri Goktug; Yaprak, HasbiAerated concrete is a lightweight concrete which has porous structure. In this study, effects of usage of sepioliteas a raw material instead of quartzite on the thermal and compressive strength properties of aerated concrete were investigated.G2/04 class aerated concrete, which has been commercially produced as a wall component, has been focused. Aerated concrete samples have been prepared by substitution of sepiolite instead of quartzite in %5, %10, %15, %20 and %25. Sepiolite has been provided from Eskisehir mine field. After 4 hours cure at 60 degrees C, samples moved to treat in autoklave in the temperature of 180 degrees C and pressure at 11 bar for 6.5 hours. Thermal conductivity and compressive strength properties of samples were determined. As a result, increasing the rate of sepiolite in aerated concrete decreases the compressive strength and increases the thermal conductivity.
