WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 10Citation - Scopus: 11Meteorological Drought Analysis for Helmand River Basin, Afghanistan(TMMOB İnşaat Mühendisleri Odası, 2022) Alami, Mohammad Musa; Tayfur, GökmenThis study evaluates drought at Lashkargah, Farah, Adraskan, and Gardandiwal stations in Helmand River Basin (HRB) in Afghanistan to determine appropriate drought indices for the basin. Thirty seven years of monthly recorded precipitation data from 1979 to 2015 are employed with different drought index (DI) methods which include the Standardized Precipitation Index (Normal-SPI, Log-SPI, and Gamma-SPI), the Percent of Normal (PN), and the Deciles. All the methods are applied to the annual long term precipitation data. The log-SPI and the gamma-SPI predict extreme drought conditions, whereas, the normal-SPI determines wet and less dry conditions. The results emphasize that the PN and the Deciles methods predict more drought years in comparison to the SPI methods. The Deciles method shows longer period of extreme and severe drought than other methods. The five methods indicate various drought intensities in 1985, 1987, 1994, 1997, 1999, 2000, 2001, 2002, 2003, and 2004 at all the stations. The extreme drought condition in 2001 at all the stations confirms to the recorded drought reports for the same region. It is noted that since the log-SPI and the gamma-SPI capture the historical extreme and severe drought periods successfully, these are recommended as the drought monitoring indices for Helmand River Basin.Article Citation - WoS: 1Artificial Neutral Networks To Predict Design Properties for Cemented Embankment Layers of High Speed Train Rail Ways(Foundation Cement, Lime, Concrete, 2013) Egeli, İsfendiyar; Tayfur, Gökmen; Yılmaz, E.; Uşun, HandanI. EGELI, G. TAYFUR, E. YILMAZ, H. USUN ARTIFICIAL NEURAL NETWORKS TO PREDICT DESIGN PROPERTIES FOR CEMENTED EMBANKMENT LAYERS OF HIGH SPEED TRAIN RAILWAYS Cement-Wapno-Beton, Vol. XVIII/LXXX, 2013, No 1, p. 10 High-speed train railway (HSTR) embankment is a complicated process, as it deals with high geometric design standards and material properties. In this study the replaceability of fill strata without cement prepared subgrade layer and with cement addition one is investigated. In the experiments the specimens composed of natural sand with different cement additions and two w/c ratios were used. The Plaxis-FEM (2D) program was employed to find the maximum expected total settlements of HSTR embankments with cemented subgrade layer. Furthermore, the artificial neural networks model was constructed to predict the failure stress, elasticity modulus and strains. The sensivity analysis has revealed that cement content was the most sensitive for stress and elasticity modulus predictions, while the curing age of specimens was for the strain forecast.Article Citation - WoS: 2Citation - Scopus: 3Rijit Gövdeli Bitkilerin Neden Olduğu Manning Katsayısının Araştırılması(Turkish Chamber of Civil Engineers, 2015) Yerdelen, Cahit; Mertsoy, Mesut; Tayfur, GökmenDoğal akış yatakları veya yapay taşkın yataklarında akım incelenirken bitkilerin sebep olduğu direnç kuvvetinin bir eşitlik yardımıyla belirlenmesi önemli bir konudur. Manning, Chezy, Darcy-Weisbach gibi eşitliklerde kullanılan direnç katsayıları, daha çok çeper özelliklerini temsil eden deneysel katsayılardır. Açık kanal şartlarında var olan veya akış kesitini kontrol etme amaçlı insanoğlunun planladığı bitkisel akış alanlarında akım hızının, su derinliğinin veya akış hacminin ampirik olarak çözülmesi planlama ve işletme süreçlerini olumlu yönde etkileyecektir. Bu çalışmada, akış kesitinde oluşacak direnç kuvvetinin, bitkilerin ve akışın fiziksel şartlarına bağlı olarak nasıl değiştiği incelenmiş ve doğrusal olmayan bir regresyon modeli önerilmiştir.Article Citation - WoS: 5Citation - Scopus: 7Experimental and Modeling Study of Strength of High Strength Concrete Containing Binary and Ternary Binders(Foundation Cement, Lime, Concrete, 2011) Erdem, Tahir Kemal; Tayfur, Gökmen; Kırca, ÖnderSilica fume (SF), fl y ash (FA) and ground granulated blastfurnace slag (S) are among the most widely utilized mineral additions for normal strength concrete (NSC) and high strength concrete (HSC). High Reactivity Metakaolin (HRMK) is a relatively new mineral addition, produced by calcination of highly pure kaolin. The replacement of cement with HRMK increases the strength, especially at early ages, and improves durability of concrete. (1-3). Pumice (P) is a porous volcanic glass containing 60-75 SiO2% and 13-17% Al2O3. When fi nely ground, it shows pozzolanic characteristics but it is generally used as a lightweight aggregate in the concrete industry (4, 5). HRMK and P have white color and, therefore, are useful for production of white concrete when applied with white Portland cement (WPC)Article Citation - WoS: 1Citation - Scopus: 1Estimation of Mechanical Properties of Limestone Using Regression Analyses and Ann(Foundation Cement, Lime, Concrete, 2012) Teomete, Egemen; Tayfur, Gökmen; Aktaş, EnginEstimation of mechanical properties of rocks is important for researchers and field engineers working in cement and concrete industry. Limestone is used in cement production. In this study, Schmidt hammer, ultrasonic pulse velocity, porosity, uniaxial compression and indirect tension tests were conducted on limestone obtained from a historical structure. Regression analyses were used to develop models relating mechanical properties of limestone. Artificial Neural Network (ANN) was performed to determine the mechanical properties. The performance of regression models and ANN were compared by existing models in the literature. The results showed that the regression models and ANN yield satisfactory performance with minimum error. The regression models between tensile strength and wave velocity, tensile strength and porosity, wave velocity and porosity have been developed for the first time in literature. The ANN is used for the first time to estimate the mechanical properties of limestone. The use of separate training and testing sets in the regression analyses of mechanical properties of limestone is conducted for the first time. The models developed in this study can be used by researchers and field engineers to relate the mechanical properties of limestone.Article Citation - WoS: 4Citation - Scopus: 3Baraj Yıkılması Sonrası İki Boyutlu Taşkın Yayılımının Yerleşim Bölgeleri için Modellenmesi(Turkish Chamber of Civil Engineers, 2017) Elçi, Şebnem; Tayfur, Gökmen; Haltaş, İsmail; Kocaman, BülentHer ne kadar baraj yıkılması nadiren gerçekleşse de, aniden yıkılan bir barajın taşkın dalgasının mansapta bulunan yerleşim bölgelerinde etkisi felaketle sonuçlanabilmektedir. Bu sebeble muhtemel bir baraj yıkılmasının sonuçlarını öngörmek risk yönetimi açısından gereklidir. Bu çalışmada baraj yıkılması sonucunda oluşan taşkın dalgasının tahmini ve mansapta ilerlemesinin analizine yönelik bir yaklaşım sunulmuştur. Sunulan yaklaşım, barajların aniden yıkılma varsayımı ile baraj haznesindeki su hacminin bir-boyutlu model ile dar bir vadi boyunca ötelenmesini ve ötelenmiş hidrograf sınır şartı kabul edilerek mansabında yerleşim bölgeleri yer alan iki ayrı çalışma alanında taşkın dalgasının iki boyutlu yayılımının modellenmesini içermektedir. Önerilen yaklaşım mansabında Eskişehir bulunan Porsuk Barajı ile mansabında İstanbul olan Alibey Barajına uygulanmıştır.Article Citation - WoS: 2Citation - Scopus: 2Soft Computing and Regression Modelling Approaches for Link-Capacity Functions(Czech Technical University in Prague, 2016) Koşun, Çağlar; Tayfur, Gökmen; Çelik, Hüseyin MuratLink-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0:87 while this value was almost 0.60 for the regression-based models.Article Citation - WoS: 2Citation - Scopus: 1Significance of Rent Attributes in Prediction of Earthquake Damage in Adapazari, Turkey(Czech Technical University in Prague, 2014) Tayfur, Gökmen; Bektaş, Birkan; Duvarcı, YavuzThis paper analyses rent-based determinants of earthquake damage from an urban planning perspective with the data gathered from Adapazari, Turkey, after the disaster in 1999 Eastern Marmara Earthquake (EME). The study employs linear regression, log-linear regression, and artificial neural networks (ANN) methods for cross-verification of results and for finding out the significant urban rent attribute(s) responsible for the damage. All models used are equally capable of predicting the earthquake damage and converge to similar results even if the data are limited. Of the rent variables, the physical density is proved to be especially significant in predicting earthquake damage, while the land value contributes to building resistance. Thus, urban rent can be the primary tool for planners to help reduce the fatalities in preventive planning studies.Article Citation - WoS: 2Citation - Scopus: 2Ampirik Yöntemlerle Gediz Nehri için Askıda Katı Madde Yükü Tahmini(Turkish Chamber of Civil Engineers, 2011) Ülke, Aslı; Özkul, Sevinç; Tayfur, GökmenIt is essential to predict suspended sediment load for understanding river morphology, design of dams, water supply problems, management of reservoirs and determination of pollution levels in rivers. The suspended sediment load can be determined by means of several methods such as direct measurements at the sediment gauging stations, sediment rating curve, son modeling methods, and empirical methods which are based on experimental works. The objective of this study is first to determine the best empirical method for Gediz river and then to improve the determined method by genetic algorithm (GA). It is seen that the GA improved Brooks method can be used for Gediz River Basin. In addition, this method was compared with other soft computing (ANN, ANFIS) methods and its performance is found to be as good as them.Article Citation - WoS: 11Citation - Scopus: 12Passenger Flows Estimation of Light Rail Transit (lrt) System in Izmir, Turkey Using Multiple Regression and Ann Methods(Faculty of Transport and Traffic Sciences, University of Zagreb, 2012) Özuysal, Mustafa; Tayfur, Gökmen; Tanyel, SerhanPassenger flow estimation of transit systems is essential for new decisions about additional facilities and feeder lines. For increasing the efficiency of an existing transit line, stations which are insufficient for trip production and attraction should be examined first. Such investigation supports decisions for feeder line projects which may seem necessary or futile according to the findings. In this study, passenger flow of a light rail transit (LRT) system in Izmir, Turkey is estimated by using multiple regression and feed-forward back-propagation type of artificial neural networks (ANN). The number of alighting passengers at each station is estimated as a function of boarding passengers from other stations. It is found that ANN approach produced significantly better estimations specifically for the low passenger attractive stations. In addition, ANN is found to be more capable for the determination of trip-attractive parts of LRT lines.