Abstract
One of the most important subjects of hydraulic engineering is the reliable estimation of the transverse distribution in the rectangular channel of bed and wall shear stresses. This study makes use of the Tsallis entropy, genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) methods to assess the shear stress distribution (SSD) in the rectangular channel. To evaluate the results of the Tsallis entropy, GP and ANFIS models, laboratory observations were used in which shear stress was measured using an optimized Preston tube. This is then used to measure the SSD in various aspect ratios in the rectangular channel. To investigate the shear stress percentage, 10 data series with a total of 112 different data for were used. The results of the sensitivity analysis show that the most influential parameter for the SSD in smooth rectangular channel is the dimensionless parameter B/H, Where the transverse coordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one. Based on the analysis, it can be concluded that the use of GP and ANFIS algorithms is more effective in estimating shear stress in smooth rectangular channels than the Tsallis entropy-based equations.
Highlights
Knowledge of boundary shear stress is necessary when studying sediment transport, flow pattern around structures, estimation of scour depth and channel migration
The analysis showed that there is a lack of ability in the outcome, and it is not satisfactory
Three different models were evaluated to investigate the effect of each input parameter in the genetic programming (GP) modeling
Summary
Knowledge of boundary shear stress is necessary when studying sediment transport, flow pattern around structures, estimation of scour depth and channel migration. The determination of boundary shear stress, i.e., at the wall and bed depends on the channel geometry and its associated roughness. Various direct and indirect methods have been extensively discussed in experimentally measure the wall and bed shear stresses in channels with different cross sections [1,2,3,4]. Bed shear stress can be estimated based on four techniques (1) bed slope product τb = gHS, (2) law of the wall velocity profiles u u∗. The symbols g, H and S denote gravity, water level and channel slope, respectively, whereas u is the velocity at height z, u* is the shear velocity, k is von Karman constant and z0 is the roughness length
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