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RISS 인기검색어
- 검색키워드
- 저자 : Hossein Bonakdari (검색결과 4 건)
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Modeling of Velocity Fields by the Entropy Concept in Narrow Open Channels
Hossein Bonakdari,Marjan Moazamnia 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.3
To predict velocity field in narrow open channels, the Tsallis entropy based on probability has been developed in this paper. Givena definition of the Tsallis entropy, it is maximized by using the probability density function, which then is used to attain a velocitydistribution equation. This is then employed for calculating the velocity distribution in narrow open channel under a wide range ofdischarge and water depth, and finally, for viability, these calculations are compared with some relevant field experimental results. Bycomparing the actual field data and the model results for estimating velocity distribution, this study highlights the application of theTsallis entropy concept to predict it in narrow open channels. The obtained results showed that this theoretically generated equation isefficient for predicting the velocity distribution in narrow open channels with the maximum velocity taking place below the freesurface.
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Improved Side Weir Discharge Coefficient Modeling by Adaptive Neuro-fuzzy Methodology
Shahaboddin Shamshirband,Hossein Bonakdari,Amir Hossein Zaji,Dalibor Petkovic,Shervin Motamedi 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.7
In this article, the accuracy of a soft computing technique is evaluated in terms of discharge coefficient prediction of an improved triangular side weir. The process includes simulating the discharge coefficient with the Adaptive Neuro-Fuzzy Inference System (ANFIS). Matlab software is used for ANFIS modeling. To identify the most appropriate input variables, eight different input combinations with various numbers of inputs are examined. The performance of the proposed system is confirmed by comparing the ANFIS and experimental results for the testing dataset. The performance evaluation demonstrates that the ANFIS model with five inputs (Root Mean Square Error (RMSE) of 0.014) is more accurate than the ANFIS model with one input (RMSE = 0.088). The ANFIS model results are also compared with the results obtained from previous regression and soft computing studies.
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Isa Ebtehaj,Hossein Bonakdari 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.2
Due to the presence of solid matter in the flow passing through sewer pipes, determining the minimum velocity that prevents sediment deposition is essential. In this study, the Multilayer Perceptron (MLP) network optimized with three different training algorithms, including variable learning rate (MLP-GDX), resilient back-propagation (MLP-RP) and Levenberg-Marquardt (MLPLM) is studied in terms of ability to estimate sediment transport in a clean pipe. The results indicate that for all algorithms, model ANN(d) that uses volumetric sediment concentration (CV), median relative size of particles (d/D), ratio of median diameter particle size to hydraulic radius (d/R) and overall sediment friction factor (λs) as input parameters, is more accurate than the other models. In predicting Fr, the results of MLP-LM (R2 = 0.98, RMSE = 0.02 and MAPE = 5.13) are better than MLP-GDX (R2 = 0.96, RMSE = 0.03 and MAPE = 5.9) and MLP-RP (R2 = 0.95, RMSE = 0.26 and MAPE = 5.74). A comparison of the model selected in this study with existing equations of sediment transport in sewer pipes also indicates that ANN(d)-LM (RMSE = 0.025 & MAPE = 5.78) perform better than existing equations.
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Ali Akbar Zinatizadeh Lorestani,Hojjatollah Bashiri,Azar Asadi,Hossein Bonakdari 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.10
Wastewater from the milk industry usually undergoes activated sludge ahead of refining treatments, final discharge or reuse. To identify the most effective bioreactor hydraulic regime for the secondary treatment of wastewater resulting from the milk industry in an activated sludge system, two lab-scale activated sludge systems characterized by a different configuration and fluid dynamics (i.e., a compartmentalized activated sludge (CAS) with plug flow regime and a complete mixed activated sludge (AS)) were operated in parallel, inoculated with the same microbial consortium and fed with identical streams of a stimulated dairy wastewater. The effect of three process and operational variables--influent chemical oxygen demand (COD) concentration, sludge recycle ratio (R) and hydraulic retention time (HRT)--on the performance of the two systems were investigated. Experiments were conducted based on a central composite face-centered design (CCFD) and analyzed using response surface methodology (RSM). The region of exploration for treatment of the synthetic wastewater was taken as the area enclosed by the CODin (200, 1,000 mg/l), R (1, 5), and HRT (2, 5 h) boundaries. To evaluate the process, three parameters, COD removal efficiency (E), specific substrate utilization rate (U), and sludge volume index (SVI), were measured and calculated over the course of the experiments as the process responses. The change of the flow regime from complete-mix to plug flow resulted in considerable improvements in the COD removal efficiency of milk wastewater and sludge settling properties. SVI levels for CAS system (30-58 ml/g) were considerably smaller that for the AS system (50-145 ml/g). In addition, the biomass production yield could be reduced by about 10% compared to the AS system. The results indicated that for the wastewater, the design HRT of a CAS reactor could be shortened to 2-4 h.
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