Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 3Citation - Scopus: 3Ensemble and Optimized Hybrid Algorithms Through Runge Kutta Optimizer for Sewer Sediment Transport Modeling Using a Data Pre-Processing Approach(Elsevier, 2023) Safari, Mir Jafar Sadegh; Gül, Enes; Dursun, Ömer Faruk; Tayfur, GökmenUncontrolled sediment deposition in drainage and sewer systems raises unexpected maintenance expenditures. To this end, implementation of an accurate model relying on effective parameters involved is a reliable benchmark. In this study, three machine learning techniques, namely extreme learning machine (ELM), multilayer perceptron neural network (MLPNN), and M5P model tree (M5PMT); and three optimization approaches of Runge Kutta (RUN), genetic algorithm (GA), and particle swarm optimization (PSO) are applied for modeling. The optimization and ensemble hybridization approaches are applied in the modeling procedure. For the case of hybrid optimized models, the ELM and MLPNN models are hybridized with RUN, GA, and PSO algorithms to develop six hybrid models of ELM-RUN, ELM-GA, ELM-PSO, MLPNN-RUN, MLPNN-GA, and MLPNN-PSO. Ensemble hybrid models are developed through coupling the ELM and MLPNN models with the M5PMT algorithm. The data pre-processing approach is applied to find the best randomness characteristic of the utilized data. Results illustrate that the RUN-based hybrid models outperform the GA- and PSO-based counterparts. Although the MLPNN-RUN and MLPNN-M5PMT hybrid models generate better results than their alternatives, MLPNN-M5PMT slightly outperforms MLPNN-RUN model with a coefficient of determination of 0.84 and a root mean square error of 0.88. The current study shows the superiority of the ensemble-based approach to the optimization techniques. Further investigation is needed by considering alternative optimization techniques to enhance sediment transport modeling. © 2023 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion ResearchArticle Citation - WoS: 10Citation - Scopus: 11Transport Capacity Models for Unsteady and Non-Equilibrium Sediment Transport in Alluvial Channels(Elsevier Ltd., 2012) Tayfur, Gökmen; Singh, Vijay P.This study investigates transport capacity models based on different dominant variables-shear stress, stream power, unit stream power, flow discharge, flow velocity, and energy slope - in a model of unsteady and non-equilibrium sediment transport in alluvial channels. The model simulates fully coupled system of water flow, suspended sediment, and bed load sediment transport processes in two-layer system of water flow phase and movable bed. The model employs conservation of mass equation for the water in both the layers; suspended sediment in the water flow phase; sediment in the movable bed layer; and the momentum equation for the water flow in the flow phase. The system is closed by relating the sediment flux in the movable bed layer to the sediment concentration in the same layer by employing the kinematic wave theory. Using the sediment transport capacity expression with different dominant variables, a series of numerical experiments are carried out for unsteady and non-equilibrium sediment transport. The results seem theoretically reasonable for hypothetical cases. The model is calibrated and validated using different experimental data sets. The calibrated value for the transport capacity model's exponent (ki) is found to be 1.50, 1.65, 0.24, 0.56, 4.80, and 0.22 for shear stress, stream power, unit stream power, discharge, velocity, and slope approaches, respectively. The numerical investigation results show that transport capacity model based on any dominant variable can be employed for modelling unsteady and non-equilibrium sediment transport.Article Citation - WoS: 60Citation - Scopus: 69Experimental and Numerical Investigation of Bed-Load Transport Under Unsteady Flows(American Society of Civil Engineers (ASCE), 2011) Bombar, Gökçen; Elçi, Şebnem; Tayfur, Gökmen; Güney, M. Şükrü; Bor, AslıThe dynamic behavior of bed-load sediment transport under unsteady flow conditions is experimentally and numerically investigated. A series of experiments are conducted in a rectangular flume (18 m in length, 0.80 m in width) with various triangular and trapezoidal shaped hydrographs. The flume bed of 8 cm in height consists of scraped uniform small gravel of D 50=4.8 mm. Analysis of the experimental results showed that bed-load transport rates followed the temporal variation of the triangular and trapezoidal hydrographs with a time lag on the average of 11 and 30 s, respectively. The experimental data were also qualitatively investigated employing the unsteady-flow parameter and total flow work index. The analysis results revealed that total yield increased exponentially with the total flow work. An original expression which is based on the net acceleration concept was proposed for the unsteadiness parameter. Analysis of the results then revealed that the total yield increased exponentially with the increase in the value of the proposed unsteadiness parameter. Further analysis of the experimental results revealed that total flow work has an inverse exponential variation relation with the lag time. A one-dimensional numerical model that employs the governing equations for the conservation of mass for water and sediment and the momentum was also developed to simulate the experimental results. The momentum equation was approximated by the diffusion wave approach, and the kinematic wave theory approach was employed to relate the bed sediment flux to the sediment concentration. The model successfully simulated measured sedimentographs. It predicted sediment yield, on the average, with errors of 7% and 15% of peak loads for the triangular and trapezoidal hydrograph experiments, respectively.Article Citation - WoS: 16Citation - Scopus: 18Kinematic Wave Model of Bed Profiles in Alluvial Channels(John Wiley and Sons Inc., 2006) Tayfur, Gökmen; Singh, Vijay P.A mathematical model, based on the kinematic wave (KW) theory, is developed for describing the evolution and movement of bed profiles in alluvial channels. The model employs a functional relation between sediment transport rate and concentration, a relation between flow velocity and depth and Velikanov's formula relating suspended sediment concentration to flow variables. Laboratory flume and field data are used to test the model. Transient bed profiles in alluvial channels are also simulated for several hypothetical cases involving different water flow and sediment concentration characteristics. The model-simulated bed profiles are found to be in good agreement with what is observed in the laboratory, and they seem theoretically reasonable for hypothetical cases. The model results reveal that the mean particle velocity and maximum concentration (maximum bed form elevation) strongly affect transient bed profiles.Article Citation - WoS: 10Citation - Scopus: 14Numerical Model for Sediment Transport Over Nonplanar, Nonhomogeneous Surfaces(American Society of Civil Engineers (ASCE), 2004) Tayfur, Gökmen; Singh, Vijay P.Sediment transport on surfaces with spatially variable microtopography, roughness, and infiltration was investigated using the diffusion wave equation. An implicit finite-difference scheme together with multivariate Newton's method was employed to solve the equation numerically. The simulation results showed that microtopography and roughness were the dominant factors causing significant spatial variations in sediment concentration. If the spatially varying microtopography was replaced by an average constant slope, the result was an overestimation of the sediment load. On the other hand, when the spatially varying roughness was replaced by the average roughness and the spatially varying infiltration rate by the average infiltration rate, the sediment discharge was not significantly affected. The sedimentograph reached an equilibrium much sooner when a constant infiltration rate was substituted for the time-varying infiltration rate.Article Citation - WoS: 68Citation - Scopus: 86Fuzzy Logic Algorithm for Runoff-Induced Sediment Transport From Bare Soil Surfaces(Elsevier Ltd., 2003) Tayfur, Gökmen; Özdemir, Serhan; Singh, Vijay P.Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relations among rainfall intensity, slope, and sediment transport were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF-THEN format. The commonly used weighted average method was employed for the defuzzification procedure. The sediment load predicted by the fuzzy model was in satisfactory agreement with the measured sediment load data. Predicting the mean sediment loads from experimental runs, the performance of the fuzzy model was compared with that of the artificial neural networks (ANNs) and the physics-based models. The results of showed revealed that the fuzzy model performed better under very high rainfall intensities over different slopes and over very steep slopes under different rainfall intensities. This is closely related to the selection of the shape and frequency of the fuzzy membership functions in the fuzzy model.Article Citation - WoS: 36Citation - Scopus: 43Applicability of Sediment Transport Capacity Models for Nonsteady State Erosion From Steep Slopes(American Society of Civil Engineers (ASCE), 2002) Tayfur, GökmenThe physics-based sediment transport equations are derived from the assumption that the sediment transport rate can be determined by a dominant variable such as flow discharge, flow velocity, slope, shear stress, stream power, and unit stream power. In modeling of sheet erosion/sediment transport, many models that determine the transport capacity by one of these dominant variables have been developed. The developed models mostly simulate steady-state sheet erosion. Few models that are based on the shear-stress approach attempt to simulate nonsteady state sheet erosion. This study qualitatively investigates the applicability of the transport capacity models that are based on one of the commonly employed dominant variables-unit stream power, stream power, and shear stress-to simulate nonsteady state sediment loads from steep slopes under different rainfall intensities. The test of the calibrated models with observed data sets shows that the unit stream power model gives better simulation of sediment loads from mild slopes. The stream power and the shear stress models, on the other hand, simulate sediment loads from steep slopes more satisfactorily. The exponent (ki) in the sediment transport capacity formula is found to be 1.2, 1.9, and 1.6 for the stream power model, the shear stress model, and the unit stream power model, respectively.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.