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Emin M Emiroglu - One of the best experts on this subject based on the ideXlab platform.
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determination of capacity of labyrinth side weir by cfd
Flow Measurement and Instrumentation, 2013Co-Authors: Cihan M Aydin, Emin M EmirogluAbstract:Abstract Side weirs are widely used in irrigation, Land Drainage, urban sewage systems, flood protection, and forebay pool of hydropower systems by flow diversion or intake devices. The hydraulic behavior of side weirs received considerable interest by many researchers. A large number of these studies are physical model tests of rectangular side weirs. However, in the study, Computational Fluid Dynamics (CFD) models together with laboratory models of labyrinth side weirs were used for determining the discharge capacity of the labyrinth side weir located on the straight channel. The discharges performances obtained from CFD analyses were compared with the observed results for various Froude number, dimensionless nappe height, dimensionless weir width, and weir included angle. The results obtained from both methods are in a good agreement.
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discharge coefficient of side weirs in curved channels
Proceedings of the Institution of Civil Engineers - Water Management, 2012Co-Authors: Hayrullah Agaccioglu, Emin M Emiroglu, Nihat KayaAbstract:Side weirs are flow diversion devices commonly used in irrigation, Land Drainage and urban sewage systems. It is essential for hydraulic and environmental engineers involved in the design of side weirs to predict the discharge coefficient correctly. The aim of this study is to present an accurate equation for discharge coefficients along the bend of sharp-crested rectangular side weirs based on a total of 1504 experimental runs. The discharge coefficient of the rectangular side weir along the bend depends on the dimensionless parameters of Froude number in the main channel F1, the angle of bend curvature α, the ratio of weir length to main channel width L/b, the ratio of weir length to radius of main channel centreline L/rc and the ratio of weir height to upstream flow depth p/h1. In particular, the variables L/rc and p/h1 are not seen in any equation for a rectangular side weir located on a curved channel. However, it was found that these dimensionless parameters were significantly important for the over...
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neural networks for estimation of discharge capacity of triangular labyrinth side weir located on a straight channel
Expert Systems With Applications, 2011Co-Authors: Emin M Emiroglu, Omer Bilhan, Ozgur KisiAbstract:Side-weirs are flow diversion devices widely used in irrigation, Land Drainage, and urban sewage systems. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side-weirs. In this study, the discharge capacity of triangular labyrinth side-weirs is estimated by using artificial neural networks (ANN). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side-weirs. The performance of the ANN model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the neural computing technique could be employed successfully in modelling discharge coefficient from the available experimental data. There were good agreements between the measured values and the values obtained using the ANN model. It was found that the ANN model with RMSE of 0.0674 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
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predicting discharge capacity of triangular labyrinth side weir located on a straight channel by using an adaptive neuro fuzzy technique
Advances in Engineering Software, 2010Co-Authors: Emin M Emiroglu, Ozgur Kisi, Omer BilhanAbstract:Side weirs are widely used for flow diversion in irrigation, Land Drainage, urban sewage systems and also in intake structures. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side weirs. In this study, the discharge capacity of triangular labyrinth side weirs is estimated by using adaptive neuro-fuzzy inference system (ANFIS). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side weirs. The performance of the ANFIS model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the ANFIS technique could be employed successfully in modeling discharge coefficient from the available experimental data. There are good agreements between the measured values and the values obtained using the ANFIS model. It is found that the ANFIS model with RMSE of 0.0699 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
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discharge capacity of labyrinth side weir located on a straight channel
Journal of Irrigation and Drainage Engineering-asce, 2010Co-Authors: Nihat Kaya, Hayrullah Agaccioglu, Emin M EmirogluAbstract:Side weirs, also known as lateral weirs, are flow diversion devices widely used in irrigation as a head regulator of distributaries and escapes, Land Drainage, and urban sewage systems. The studies on the subject have been generally focused on rectangular and triangular side weirs located on a straight channel. However, the same is not true for labyrinth side weirs. The current studies deal with sediment transport and scour problems around side weirs and lateral structures. The investigation of the hydraulic effects of labyrinth side weirs to increase discharge capacity of them has been studied in this particular work. In the study, 2,830 laboratory tests were conducted for determining discharge coefficient of labyrinth side weirs, and results were analyzed to find the influence of the dimensionless weir length L/b , the dimensionless effective length L/l , the dimensionless weir height p/ h1 , triangular labyrinth side weir included angle θ , and upstream Froude number F1 on the discharge coefficient, wa...
Ozgur Kisi - One of the best experts on this subject based on the ideXlab platform.
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modeling soil cation exchange capacity using soil parameters
Computers and Electronics in Agriculture, 2017Co-Authors: Jalal Shiri, Ozgur Kisi, Ali Keshavarzi, Ursula Iturraranviveros, Ali Bagherzadeh, Rouhollah Mousavi, Sepideh KarimiAbstract:We modeled soil CEC using easily measured parameters.Heuristic models were applied for modeling CEC through using k-fold testing.k-fold testing assessing methodology provides much better insight about the models accuracy.Neuro-fuzzy surpasses GEP, NN and SVM in modeling CEC. Accurate knowledge about soil cation exchange capacity (CEC) is very important in Land Drainage and reclamation, groundwater pollution studies and modeling chemical characteristics of the agricultural Lands. The present study aims at developing heuristic models, e.g. gene expression programming (GEP), neuro-fuzzy (NF), neural network (NN), and support vector machine (SVM) for modeling soil CEC using soil parameters. Soil characteristic data including soil physical parameters (e.g. silt, clay and sand content), organic carbon, and pH from two different sites in Iran were utilized to feed the applied heuristic models. The models were assessed through a k-fold test data set scanning procedures, so a complete scan of the possible train and test patterns was carried out at each site. Comparison of the models showed that the NF outperforms the other applied models in both studied sites. The obtained results revealed that the performance of the applied models fluctuated throughout the test stages and between two sites, so a reliable assessment of the model should consider a complete scan of the utilized data set, which will be a good option for preventing partially valid conclusions obtained from assessing the models based on a simple data set assignment.
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neural networks for estimation of discharge capacity of triangular labyrinth side weir located on a straight channel
Expert Systems With Applications, 2011Co-Authors: Emin M Emiroglu, Omer Bilhan, Ozgur KisiAbstract:Side-weirs are flow diversion devices widely used in irrigation, Land Drainage, and urban sewage systems. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side-weirs. In this study, the discharge capacity of triangular labyrinth side-weirs is estimated by using artificial neural networks (ANN). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side-weirs. The performance of the ANN model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the neural computing technique could be employed successfully in modelling discharge coefficient from the available experimental data. There were good agreements between the measured values and the values obtained using the ANN model. It was found that the ANN model with RMSE of 0.0674 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
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predicting discharge capacity of triangular labyrinth side weir located on a straight channel by using an adaptive neuro fuzzy technique
Advances in Engineering Software, 2010Co-Authors: Emin M Emiroglu, Ozgur Kisi, Omer BilhanAbstract:Side weirs are widely used for flow diversion in irrigation, Land Drainage, urban sewage systems and also in intake structures. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side weirs. In this study, the discharge capacity of triangular labyrinth side weirs is estimated by using adaptive neuro-fuzzy inference system (ANFIS). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side weirs. The performance of the ANFIS model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the ANFIS technique could be employed successfully in modeling discharge coefficient from the available experimental data. There are good agreements between the measured values and the values obtained using the ANFIS model. It is found that the ANFIS model with RMSE of 0.0699 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
M Horton - One of the best experts on this subject based on the ideXlab platform.
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impact of Land Drainage on peatLand hydrology
Journal of Environmental Quality, 2006Co-Authors: Joseph Holden, Martin Evans, T P Burt, M HortonAbstract:There is a long history of Drainage of blanket peat but few studies of the long-term hydrological impact of Drainage. This paper aims to test differences in runoff production processes between intact and drained blanket peat catchments and determine whether there have been any long-term changes in stream flow since Drainage occurred. Hillslope runoff processes and stream discharge were measured in four blanket peat catchments. Two catchments were drained with open-cut ditches in the 1950s. Ditching originally resulted in shorter lag times and flashier storm hydrographs but no change in the annual catchment runoff efficiency. In the period between 2002 and 2004, the hydrographs in the drained catchments, while still flashy, were less sensitive to rainfall than in the 1950s and the runoff efficiency had significantly increased. Drains resulted in a distinctive spatial pattern of runoff production across the slopes. OverLand flow was significantly lower in the drained catchments where throughflow was more dominant. In the intact peatLands, matrix throughflow produced by peat layers below 10 cm was rare and produced ,1% of the runoff. However, in drained peatLands, matrix throughflow in deeper peat layers was common and provided around 23% of the runoff from gauged plots. Macropore flow, the density of soil piping, and pipeflow were significantly greater in drained peatLands than in intact basins. Gradual changes to peat structure could explain the long-term changes in river flow, which are in addition to those occurring in the immediate aftermath of peatLand Drainage.
Omer Bilhan - One of the best experts on this subject based on the ideXlab platform.
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neural networks for estimation of discharge capacity of triangular labyrinth side weir located on a straight channel
Expert Systems With Applications, 2011Co-Authors: Emin M Emiroglu, Omer Bilhan, Ozgur KisiAbstract:Side-weirs are flow diversion devices widely used in irrigation, Land Drainage, and urban sewage systems. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side-weirs. In this study, the discharge capacity of triangular labyrinth side-weirs is estimated by using artificial neural networks (ANN). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side-weirs. The performance of the ANN model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the neural computing technique could be employed successfully in modelling discharge coefficient from the available experimental data. There were good agreements between the measured values and the values obtained using the ANN model. It was found that the ANN model with RMSE of 0.0674 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
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predicting discharge capacity of triangular labyrinth side weir located on a straight channel by using an adaptive neuro fuzzy technique
Advances in Engineering Software, 2010Co-Authors: Emin M Emiroglu, Ozgur Kisi, Omer BilhanAbstract:Side weirs are widely used for flow diversion in irrigation, Land Drainage, urban sewage systems and also in intake structures. It is essential to correctly predict the discharge coefficient for hydraulic engineers involved in the technical and economical design of side weirs. In this study, the discharge capacity of triangular labyrinth side weirs is estimated by using adaptive neuro-fuzzy inference system (ANFIS). Two thousand five hundred laboratory test results are used for determining discharge coefficient of triangular labyrinth side weirs. The performance of the ANFIS model is compared with multi nonlinear regression models. Root mean square errors (RMSE), mean absolute errors (MAE) and correlation coefficient (R) statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it was found that the ANFIS technique could be employed successfully in modeling discharge coefficient from the available experimental data. There are good agreements between the measured values and the values obtained using the ANFIS model. It is found that the ANFIS model with RMSE of 0.0699 in validation stage is superior in estimation of discharge coefficient than the multiple nonlinear and linear regression models with RMSE of 0.1019 and 0.1507, respectively.
Davey L Jones - One of the best experts on this subject based on the ideXlab platform.
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raising the groundwater table in the non growing season can reduce greenhouse gas emissions and maintain crop productivity in cultivated fen peats
Journal of Cleaner Production, 2020Co-Authors: Yuan Wen, Benjamin Freeman, C D Evans, D R Chadwick, Huadong Zang, Davey L JonesAbstract:Abstract Fen peatLands represent a globally important carbon (C) store, while also providing highly productive agricultural Land. Drainage of these organic soils is required to create conditions suitable for crop growth, but this results in substantial greenhouse gas (GHG) emissions. One potential GHG mitigation option is to raise the groundwater table to reduce the duration and volume of peat exposure to aerobic conditions. However, the trade-off between maintaining food production and securing ecosystem function under a high water table (WT) presents a serious challenge for both Land managers and policy makers. Therefore, we conducted a controlled mesocosm experiment to investigate the effects of WT elevation (from −50 cm to −30 cm) under three contrasting scenarios: (i) WT raised throughout the year, (ii) WT raised in the winter only, and (iii) WT raised in the growing season only. We measured GHG emissions, nitrate, ammonium and dissolved organic C concentrations in soil solution, alongside the yield of a commercially important crop (lettuce). Raising the WT throughout the year reduced lettuce yields by 37% and reduced CO2 emissions by 36% without changing the loss rates of N2O or CH4. Raising the WT only in the winter did not significantly reduce crop yield, but still suppressed CO2 emissions during the fallow period (by 30%). Raising the WT only in the growing season reduced root growth and CO2 emissions (by 27%), but had no major effect on lettuce yield. In conclusion, the present study shows that raising the groundwater table in the non-growing season reduced GHG emissions without negatively affecting lettuce yields, and may therefore represent a viable GHG mitigation option for agricultural peatLands.
