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Water Science and Engineering 2018年第2期11卷 167-176页

作者： Zohreh Sheikh Khozani Hossein Bonakdari isa ebtehaj Department of Civil Engineering Razi University

The shear stress distribution in circular channels was modeled in this study using gene expression programming(GEP). 173 sets of reliable data were collected under four flow conditions for use in the training and testing stages. The effect of input variables on GEP modeling was studied and 15 different GEP models with individual, binary, ternary, and quaternary input combinations were investigated. The sensitivity analysis results demonstrate that dimensionless parameter y/P, where y is the transverse coordinate, and P is the wetted perimeter, is the most influential parameter with regard to the shear stress distribution in circular channels. GEP model 10, with the parameter y/P and Reynolds number(Re) as inputs, outperformed the other GEP models, with a coefficient of determination of 0.7814 for the testing data set. An equation was derived from the best GEP model and its results were compared with an artificial neural network(ANN) model and an equation based on the Shannon entropy proposed by other researchers. The GEP model, with an average RMSE of 0.0301, exhibits superior performance over the Shannon entropy-based equation, with an average RMSE of 0.1049, and the ANN model, with an average RMSE of 0.2815 for all flow depths.

关键词： Circular channel Gene expression programming(GEP) Sensitivity analysis Shear stress distribution Soft computing

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An analysis of shear stress distribution in circular channels with sediment deposition based on Gene Expression Programming

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International Journal of Sediment Research 2017年第4期32卷 575-584页

作者： Zohreh Sheikh Khozani Hossein Bonakdari isa ebtehaj Department of Civil Engineering Razi University

Knowledge of the boundary shear stress distribution in channels is important because it is a key factor affecting on erosion and sedimentation rates. The presence of sediment deposits in sewers is often reported during operation, and circular channels are frequently used in sewer networks. Gene expression programming(GEP) is applied in this study to determine an equation for evaluating the shear stress distribution along the wetted perimeter of a circular channel with a flat bed, because of the presence of sediment on the bed. In view of the parameters affecting the shear stress distribution, five dimensionless parameters are applied to develop six GEP models to be used with 905 experimental data. The impact of the shear stress parameters is studied using the six GEP models and by dividing the wetted perimeter into wall and bed sections. Two equations are extracted from the GEP models' output to estimate wall and bed shear stresses. The best model results are compared with a well-known equation based on the entropy concept. The GEP model predictions of wall and bed shear stresses are very similar to the experimental outcomes, whereas the entropy-based model overestimates the shear stress *** proposed GEP models demonstrate superior performance in estimating the shear stress distribution with a mean absolute percentage error(MAPE) of 3.79% compared to an existing equation with MAPE of 9.52%.

关键词： Circular channel Gene Expression Programming(GEP) Shannon entropy Shear stress distribution Sediment

基于自清洁理念的下水道中沉积物运移的设计标准(英文)

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2014年第11期15卷 914-924页

作者： isa ebtehaj Hossein BONAKDARI Ali SHARIFI Department of Civil Engineering Razi University Department of Statistics Razi University

研究目的:通过比较沉积物运移的不同标准,经选优得出更高精度的标准。创新要点:使用更少的参数和分情况来获得高精度的设计标准。研究方法:1.按状态将下水道中沉积物分成两类:没有沉淀的沉积物和沉淀的推移质;2.利用已有设计标准的方程... 详细信息

研究目的:通过比较沉积物运移的不同标准,经选优得出更高精度的标准。创新要点:使用更少的参数和分情况来获得高精度的设计标准。研究方法:1.按状态将下水道中沉积物分成两类:没有沉淀的沉积物和沉淀的推移质;2.利用已有设计标准的方程,运用非线性回归和MINITAB软件,得到不同情况下的最佳方程式;3.用实验所得的值对各方程预测值进行验证,比较各方程式的预测精度。重要结论:1.本文提出的方程式可以预测不同情况下的沉积物运移;2.相比于其它标准,本文提出的方程式形式简单、所需参数少和参数估计简单,并且预测精度更高。

关键词：沉积床推移质沉积限制沉积物下水道

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Determining the Scour Dimensions Around Submerged Vanes in a 180°Bend with the Gene Expression Programming Technique

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Journal of Marine Science and Application 2018年第2期17卷 233-240页

作者： Saeid Shabanlou Hamed Azimi isa ebtehaj Hossein Bonakdari Department of Water Engineering Kermanshah BranchIslamic Azad UniversityKermanshah 67146Iran Department of Civil Engineering Razi UniversityKermanshah 67146Iran Environmental Research Center Razi UniversityKermanshah 67146Iran

Submerged vanes are installed on rivers and channel beds to protect the outer bank bends from ***,local scouring occurs around the submerged vanes over time,and identifying the effective factors on the scouring phenomena around these submerged vanes is one of the important issues in river *** most important aimof this study is investigation of scour pattern around submerged vanes located in 180°bend experimentally and ***,the effects of various parameters such as the Froude number(Fr),angle of submerged vanes to the flow(α),angle of submerged vane location in the bend(θ),distance between submerged vanes(d),height(H),and length(L)of the vanes on the dimensionless volume of the scour hole were experimentally *** submerged vanes were installed on a 180°bend whose central radius and channel width were 2.8 and 0.6 m,*** reducing the Froude number,the scour hole volume *** all Froude numbers,the biggest scour hole formed atθ=15°.In all models,by increasing the Froude number,the scour hole volume significantly *** addition,by increasing the submerged vanes’length and height,the scour hole dimensions also ***,using gene expression programming(GEP),a relationship for determining the scour hole volume around the submerged vanes was *** this model,the determination coefficients(R2)for the training and test modes were computed as 0.91 and 0.9,*** addition,this study performed partial derivative sensitivity analysis(PDSA).According to the results,the PDSA was calculated as positive for all input variables.

关键词： 180°bend Submerged vanes Scour hole volume Gene expression programming Partial derivative sensitivity analysis

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Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

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International Journal of Sediment Research 2020年第2期35卷 157-170页

作者： isa ebtehaj Hossein Bonakdari Mir Jafar Sadegh Safari Bahram Gharabaghi Amir Hossein Zaji Hossien Riahi Madavar Zohreh Sheikh Khozani Mohammad Sadegh Es-haghi Aydin Shishegaran Ali Danandeh Mehr Department of Civil Engineering Razi University Environmental Research Center Razi University Department of Civil Engineering Yasar University 4. School of EngineeringUniversity of Guelph 5. Department of Water EngineeringVali-e-Asr University of Rafsanjan 6. Smart and Sustainable Township Research CenterFaculty of Engineering&Built EnvironmentUniversiti Kebangsaan Malaysia 7. School of Civil EngineeringK.N.Toosi University of Technology 8. Department of Waterand EnvironmentalIran University of Science and Technology 9. Department of Civil EngineeringAntalya Bilim University

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering ***,the limiting velocity should be determined to keep the channel bottom clean from sediment ***,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many *** current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology based on the combination of sensitivity and uncertainty analyses with a machine learning technique is proposed as a tool for selection of the best input combination for modeling process at non-deposition conditions of sediment *** one to seven dimensionless parameters,127 models are developed in the current *** order to evaluate the different parameter co mbinations and select the training and te sting data,four strategies are *** the densimetric Froude number(Fr) as the dependent parameter,a model with independent parameters of volumetric sediment concentration(CV) and relative particle size(d/R) gave the best results with a mean absolute relative error(MARE) of 0.1 and a root means square error(RMSE) of *** analysis is applied with a machine learning technique to investigate the credibility of the proposed *** percentage of the observed sample data bracketed by95% predicted uncertainty bound(95 PPU) is computed to assess the uncertainty of the best models.

关键词： Non-deposition Sediment transport Sensitivity analysis Sewer Uncertainty analysis Urban drainage