Effect of Channel Boundary Conditions in Predicting Hydraulic Jump Characteristics using an ANFIS-Based Approach

Hydraulic jump is a phenomenon which is used to dissipate the kinetic energy of the flow and prevent scour below overflow spillways, chutes and sluices. This paper applies adaptive neuro-fuzzy inference system (ANFIS) as a Meta model approach to estimate hydraulic jump characteristics in channels with different bed conditions (i.e. channels with different shapes and appurtenances). In hydraulic jump characteristics modeling, different input combinations were developed and tested using 1700 experimental data. The obtained results indicated that the applied method has high capability in modeling hydraulic jump characteristics. It was observed that the developed models for expanding channel with a block performed more successful than other channels. For rectangular channels, it was found that the basin with rough bed led to better predictions compared to the basin with a step. In the prediction of jump length, the superior performance was obtained for the model with input combinations of Froude number and the relative height of jump. From the sensitivity analysis, it was induced that, Fr1 (upstream Froude number) is the most significant parameter in modeling process. Also comparison between ANFIS and semi-empirical equations indicated the great performance of the ANFIS

Evaluation of genetic programming-based models for simulating friction factor in alluvial channels

International audienceThe bed resistance is one of the most complex aspects of water flow studies in natural streams. Most of the existing non-linear formulas for describing alluvial channel flows are based on dimensional analysis and statistical fitting of data to the parameters considered in the functional relationships implicitly, which are partially valid. The present study aims at developing genetic programming (GP) - based formulation of Manning roughness coefficient in alluvial channels. The training and testing data are selected from original experiments, performed in a hydraulic flume using a sand mobile bed. A comparison was also made between GP and traditional nonlinear approaches of resistance modeling. The obtained results revealed the GP capability in modeling resistance coefficient of alluvial channels' be

Studying of flow model and bed load transport in a coarse bed river: case study - Aland River, Iran

International audienceThis paper describes a mathematical model which solves the 1D unsteady flow over a mobile bed. The model is based on the Richtmyer second-order explicit scheme. Comparison of the model results with the experimental flume data for alluvial steady flow (aggradation due to overloading) and unsteady flow shows that, by using the two-step method of Richtmyer, one can solve the equations, governing the phenomenon, in a coupled method with the desired accuracy. Firstly, the Badalan reach located at the Aland River is considered. Variations of flow rate, water level and bed level profiles due to flood hydrographs are assessed. Secondly, bed load discharge data were collected from the Aland River and a variety of bed load discharge formulae were compared with measured data. Results show that, by using the grain size of the bed surface layer to predict the bed load discharge, a larger relative error will occur compared to the other two cases and a proper choice of grain size has the main role in reduction of the relative error of bed load discharge estimation in gravel bed rivers. The applicability of formulae varies depending on flow rate, and should be split into low and high flow transport formula

MathIOmica: An Integrative Platform for Dynamic Omics

Job file for the creation/design of stained glass from either the Charles J. Connick Studio (1912-1945) or the Charles J. Connick Associates studio (1945-1986). The job file contains a job number, location information, date of completion, size, contact information, price, and a description of the project. This particular job file contains information on a job located at: Springfield, Massachusetts. Saint Michael's Church