Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 28Citation - Scopus: 30Hydrochemical and Isotopic Composition of Tuzla Geothermal Field (canakkale-Turkey) and Its Environmental Impacts(Taylor and Francis Ltd., 2009) Baba, Alper; Yüce, Galip; Deniz, Ozan; Yasin, DidemTuzla is an active geothermal area located in northwestern Turkey, 80 km south of the city of Canakkale and 5 km from the Aegean Coast. Geothermal brine, deriving from this area, contains an abundance of NaCl and a water temperature of 173°C (T1 well at 814 m depth) is typically encountered. The aim of this study was to determine the hydrogeochemical properties of the geothermal brine using both chemical and isotopic data, and to investigate the origin of the geothermal brine in the Tuzla area and the environmental impacts of Tuzla Geothermal Field (TGF). Both geothermal brine and shallow groundwater in the area are of meteoric origin. Isotope results indicate that the hot saline waters (brine) in the Tuzla geothermal field originate from connate water along faults. As the saline water rises to the surface, it mixes with shallow groundwaters in various ratios. In addition, the high sodium (Na) and chloride (Cl) content in the Tuzla Stream, fed from the Tuzla geothermal brine during the dry season, cause an increase in sodium and chloride concentrations in the shallow groundwaters by infiltration into the aquifer. Moreover, salt accumulation on the surface is observed due to the uncontrolled artesian flow of geothermal brine, which adversely affects the salinity of shallow groundwater.Article Citation - WoS: 19Citation - Scopus: 19Using Numerical Models and Acoustic Methods To Predict Reservoir Sedimentation(Taylor and Francis Ltd., 2009) Elçi, Şebnem; Bor, Aslı; Çalışkan, AnılThis study draws on drainage basin hydrography, numerical modeling and geographic information system (GIS) techniques in concert with dual frequency echo sounder data to estimate sediment thickness when initial surveys are unavailable or inaccurate. Tahtali Reservoir (Turkey), which provides 40% of water supply to the city of Izmir, was selected as the study site. Deposition patterns within the whole lake were estimated with a 3-D hydrodynamic and sediment transport model applied to Tahtali Reservoir. The numerical model simulated lake response to wind forcing and inflows and/or outflows and was used to describe sediment deposition patterns resulting from the erosion of soils quantified by the implementation of Universal Soil Loss Equation (USLE) to the whole watershed. Surveying of the lake via dual frequency (28/200 kHz) echo sounder system revealed the current bathymetry, and sediment thickness was estimated from the difference of depths measured by the dual frequency sounder along surveyed transects. These results were compared to the modeled sedimentation thicknesses and to preliminary estimates of watershed sediment yield estimated by USLE. Results of this study can be used for further water quality studies and for long term management plans.Article Citation - WoS: 5Citation - Scopus: 8Forecasting Interregional Commodity Flows Using Artificial Neural Networks: an Evaluation(Taylor and Francis Ltd., 2004) Çelik, Hüseyin MuratPrevious studies have concluded that the use of artificial neural networks (ANNs) is a promising new technique for modelling freight distribution, supporting, the findings of other studies in the area of spatial interaction modelling. However, the forecasting performance of ANNs is still under investigation. This study tests the predictive performance of the ANN Model with respect to a Box-Cox spatial interaction model. It is concluded that the Box-Cox model outperforms ANN in forecasting interregional commodity flows even if ANN had proven calibration superiority in comparison to conventional gravity type models.Conference Object Citation - WoS: 1Citation - Scopus: 6Genetic Algorithm-Artificial Neural Network Model for the Prediction of Germanium Recovery From Zinc Plant Residues(Taylor and Francis Ltd., 2002) Akkurt, Sedat; Özdemir, Serhan; Tayfur, GökmenA multi-layer, feed-forward, back-propagation learning algorithm was used as an artificial neural network (ANN) tool to predict the extraction of germanium from zinc plant residues by sulphuric acid leaching. A genetic algorithm (GA) was used for the selection of training and testing data and a GA-ANN model of the germanium leaching system was created on the basis of the training data. Testing of the model yielded good error levels (r2 = 0.95). The model was employed to predict the response of the system to different values of the factors that affect the recovery of germanium and the results facilitate selection of the experimental conditions in which the optimum recovery will be achieved.Article Citation - WoS: 150Citation - Scopus: 171Artificial Neural Networks for Sheet Sediment Transport(Taylor and Francis Ltd., 2002) Tayfur, GökmenSheet sediment transport was modelled by artificial neural networks (ANNs). A three-layer feed-forward artificial neural network structure was constructed and a back-propagation algorithm was used for the training of ANNs. Event-based, runoff-driven experimental sediment data were used for the training and testing of the ANNs. In training, data on slope and rainfall intensity were fed into the network as inputs and data on sediment discharge were used as target outputs. The performance of the ANNs was tested against that of the most commonly used physically-based models, whose transport capacity was based on one of the dominant variables-flow velocity (V), shear stress (SS), stream power (SP), and unit stream power (USP). The comparison results revealed that the ANNs performed as well as the physically-based models for simulating nonsteady-state sediment loads from different slopes. The performances of the ANNs and the physically-based models were also quantitatively investigated to estimate mean sediment discharges from experimental runs. The investigation results indicated that better estimations were obtained for V over mild and steep slopes, under low rainfall intensity; for USP over mild and steep slopes, under high rainfall intensity; for SP and SS over very steep slopes, under high rainfall intensity; and for ANNs over steep and very steep slopes, under very high rainfall intensities.Article Citation - WoS: 29Citation - Scopus: 33Areally-Averaged Overland Flow Equations at Hillslope Scale(Taylor and Francis Ltd., 1998) Tayfur, Gökmen; Kavvas, M. LeventMicroscale-averaged inter-rill area sheet flow and rill flow equations (Tayfur and Kavvas, 1994) are averaged along the inter-rill area length and rill length to obtain local areally-averaged inter-rill area sheet flow and rill flow equations (local-scale areal averaging). In this averaging, the local areally-averaged flow depths are related to the microscale-averaged flow depths at the outlet sections (downstream ends) of a rill and an inter-rill area by the assumption that the flow in these sections has the profile of a sine function. The resulting local areally-averaged flow equations become time dependent only. To minimize computational efforts and economize on the number of model parameters, local areally-averaged flow equations are then averaged over a whole hillslope section (hillslope-scale areal averaging). The expectations of the terms containing more than one variable are obtained by the method of regular perturbation. Comparison of model results with observed data is satisfactory. The comparison of the model results with those of previously developed models which use point-scale and large-scale (transectionally) averaged technology indicates the superiority of this model over them. Microscale-averaged inter-rill area sheet flow and rill flow equations (Tayfur & Kavvas, 1994) are averaged along the inter-rill area length and rill length to obtain local areally-averaged inter-rill area sheet flow and rill flow equations (local-scale areal averaging). In this averaging, the local areally-averaged flow depths are related to the microscale-averaged flow depths at the outlet sections (downstream ends) of a rill and an inter-rill area by the assumption that the flow in these sections has the profile of a sine function. The resulting local areally-averaged flow equations become time dependent only. To minimize computational efforts and economize on the number of model parameters, local areally-averaged flow equations are then averaged over a whole hillslope section (hillslope-scale areal averaging). The expectations of the terms containing more than one variable are obtained by the method of regular perturbation. Comparison of model results with observed data is satisfactory. The comparison of the model results with those of previously developed models which use point-scale and large-scale (transectionally) averaged technology indicates the superiority of this model over them