Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Citation - Scopus: 4Application of Fuzzy Logic in Water Resources Engineering(Elsevier, 2022) Tayfur, GökmenThis chapter introduces the fundamentals of fuzzy logic (FL), fuzzy sets, and fuzzy model components such as the fuzzification, the fuzzy rule base, the fuzzy inference engine, and the defuzzification. The processes of the fuzzy model components are presented by working on the examples from the water resources engineering application problems. This chapter also discusses the merits and the shortcomings of the fuzzy modeling. Hydrological processes have inherent source of uncertainty, for which the fuzzy set theory can be an effective solution tool. © 2023 Elsevier Inc. All rights reserved.Book Part Citation - Scopus: 1Developments in Sediment Transport Modeling in Alluvial Channels(Elsevier, 2022) Tayfur, GökmenThis chapter discusses the developments in the mathematical modeling of sediment transport dynamics in alluvial channels. Starting with early experimental and empirical studies, it goes on to treating the processes in 1D, 2D, and 3D uniform sediment transport. Finally, it describes the treatment of the processes in 3D nonuniform sediment transport considering turbulence effects. While introducing the advancements in mathematical modeling of the dynamics, the chapter also discusses the outstanding issues like the treatment of the particle fall velocity, the particle velocity, and sediment transport rate function. © 2023 Elsevier Inc. All rights reserved.Book Part Citation - Scopus: 3Real-Time Flood Hydrograph Predictions Using Rating Curve and Soft Computing Methods (ga, Ann)(Elsevier, 2022) Tayfur, GökmenThis chapter introduces hydraulic and hydrologic flood routing methods in natural channels. It details hydrological flood routing methods of the Rating Curve and Muskingum. Based on the rating curve method (RCM), it presents real-time flood hydrograph predictions using the genetic algorithm (GA-based RCM) model. In addition, it presents how to make real-time flood hydrograph predictions using the artificial neural network (ANN). The chapter briefly introduces the basics of GA and details how to calibrate and validate the GA-based RCM model using measured real-time flood hydrographs. Similarly, after giving the basics of ANN, it shows how to train and test the ANN model using measured hydrographs. Real hydrograph simulations by the RCM, GA-based RCM, and ANN are presented, and merits of each model are discussed. © 2023 Elsevier Inc. All rights reserved.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: 13Citation - Scopus: 14Soil Erosion Model Tested on Experimental Data of a Laboratory Flume With a Pre-Existing Rill(Elsevier Ltd., 2020) Aksoy, Hafzullah; Gedikli, Abdullah; Yılmaz, Murat; Eriş, Ebru; Ünal, N. Erdem; Yoon, Jaeyoung; Tayfur, GökmenPrediction of sediment discharge transported within flow is strongly needed in order to provide measures for a well-established erosion control and water quality management practice. Initiated by runoff generation and erosion processes sediment transport is influenced by microtopography over hillslopes of hydrological watersheds. Consideration of microtopography provides more accurate results. In this study, a process-based two-dimensional rainfall-runoff mathematical model is coupled with erosion and sediment transport component. Both the rainfall-runoff and sediment transport components make simulations in rills and over interrill areas of a bare hillslope. Models at such fine resolution are rarely verified due to the complexity of rills and interrill areas. The model was applied on a data set compiled from laboratory experiments. Erosion flume was filled with granular sand to replace a bare soil. A longitudinal rill and an interrill area were pre-formed over the soil in the flume before the simulated rainfall exerted on. The flume was given both longitudinal and lateral slopes. The simulated rainfall was changed between 45 mm/h and 105 mm/h and exerted on granular uniform fine and medium sand in the erosion flume with longitudinal and lateral slopes both changing from 5% to 20%. Calibration of the model shows that it is able to produce good results in terms of sedigraphs, which suggest also that the model might be considered an important step to verify and improve watershed scale erosion and sediment transport models.