Predicting flow conditions over stepped chutes based on ANFIS

Hanbay, Davut; Baylar, Ahmet; Ozpolat, Emrah

doi:10.1007/s00500-008-0343-7

Cited by 23 publications

(7 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method has been applied in various hydraulics and hydrologie problems, for example, characteristics of scour downstream of stilling basins (Farhoudi et al 2010) and around piers (Bateni et al 2007), rainfall-runoff modelling (Gautam & Holz 2001), prediction of flow condition, and estimation of aeration efficiency in stepped spillways (Baylar et al 2007;Hanbay et al 2009). IfHishigh,andGishighThenQfli = If H is low, and G is low Then 0^2 = Pi-H + q^G + ' "2 Parameters p, q and r are optimized during the ANFIS training process.…”

Section: Genetic Fuzzy System (Gfs)mentioning

confidence: 99%

Air demand in gated tunnels – a Bayesian approach to merge various predictions

Najafi

Kavianpour

Najafi³

et al. 2011

Journal of Hydroinformatics

View full text Add to dashboard Cite

High flowrate through gated tunnels may cause critical flow conditions, especially downstream of the regulating gates. Aeration is found to be the most effective and efficient way to prevent cavitation attack.Several experimental equations are presented to predict air demand in gated tunnels; however, they are restricted to particular model geometries and flow conditions and often provide differing results. In this study the current relationships are first evaluated, and then other approaches for air discharge estimation are investigated. Three machine learning techniques are compared based on the flow measurements of eight physical models, with scales ranging from 1:12-1:20, including the fuzzy inference system (FIS), the genetic fuzzy system (GFS), and the adaptive network-based fuzzy inference system (ANFIS). The Bayesian Model Average (BMA) method is then proposed as a tool to merge the simulations from all models. The BMA provides the weighted average of the predictions, by assigning weights to each model in a probabilistic approach. The application of the BMA is found to be useful for improving the design of hydraulic structures by combining different models and experimental equations.

show abstract

Section: Genetic Fuzzy System (Gfs)mentioning

confidence: 99%

Air demand in gated tunnels – a Bayesian approach to merge various predictions

Najafi

Kavianpour

Najafi³

et al. 2011

Journal of Hydroinformatics

View full text Add to dashboard Cite

show abstract

“…tics, adaptive learning parameters are updated based on gradient learning rules. [27,29] and [25]. An ANFIS model is shown in Fig.…”

Section: Adaptive Network Based Fuzzy Inference Systemmentioning

confidence: 99%

“…In recent years, the developments in intelligent methods make them possible to use in complex systems modeling [19,1,12,16,15,14] and [25]. In this study, Adaptive Network based Fuzzy Inference Systems and Artificial Neural Networks models were developed to predict air-demand ratio (Q A /Q W ) in venturi weirs.…”

Section: Introductionmentioning

confidence: 99%

Using intelligent methods to predict air-demand ratio in venturi weirs

Özkan

Turgut

2010

Advances in Engineering Software

View full text Add to dashboard Cite

“…Recently, Emiroglu and Baylar (2003), Baylar and Emiroglu (2003, 2004, 2005, Baylar et al (2006Baylar et al ( , 2007aBaylar et al ( , 2007bBaylar et al ( , 2007cBaylar et al ( , 2008Baylar et al ( , 2010Baylar et al ( , 2011 and Hanbay et al (2009aHanbay et al ( , 2009b) did some detailed studies on the aeration efficiency of stepped chutes. However, the literature search has not identified any published analytical or physical study that investigates the effect of energy dissipation over stepped chutes on aeration efficiency.…”

Section: Introductionmentioning

confidence: 97%

The effect of flow patterns and energy dissipation over stepped chutes on aeration efficiency

2011

Self Cite

View full text Add to dashboard Cite

Stepped chutes that are commonly used for gabion weirs, river training, irrigation channels, and storm waterways have become popular in recent years mainly due to the intrinsic low-cost and the speed of construction. Stepped chutes are used also for in-stream re-aeration and in water treatment plants to enhance the air-water transfer of atmospheric gases and of volatile organic components. In a stepped chute, the provision of steps can produce significant energy dissipation. This paper seeks the effect of energy dissipation over stepped chutes on aeration efficiency. It is observed from the results that aeration efficiency increases with increasing energyloss ratio. There is higher energy dissipation in nappe flows than skimming flow situations and nappe flow regime lead to greater aeration efficiency than skimming flow regime. Moreover, regression equations are obtained relating aeration efficiency to stepped chute slope and energy-loss ratio. For this aim, genetic expression programming, a recently developed artificial intelligence technique, is used. The model equations obtained have high correlation coefficients and low minimum square error values.

show abstract

Predicting flow conditions over stepped chutes based on ANFIS

Cited by 23 publications

References 23 publications

Air demand in gated tunnels – a Bayesian approach to merge various predictions

Air demand in gated tunnels – a Bayesian approach to merge various predictions

Using intelligent methods to predict air-demand ratio in venturi weirs

The effect of flow patterns and energy dissipation over stepped chutes on aeration efficiency

Contact Info

Product

Resources

About