scholarly journals Visualization and image analysis of shear stress distribution over a fan blade

1999 ◽  
Vol 19 (Supplement2) ◽  
pp. 137-140
Author(s):  
Atsushi Nashimoto ◽  
Nobuyiki Fujisawa ◽  
Eiichi Kimura ◽  
Tsuneo Akuto
Keyword(s):  
Shear Stress ◽  
Image Analysis ◽  
Stress Distribution ◽  
Shear Stress Distribution ◽  
Fan Blade

scholarly journals Assessing Machine Learning versus a Mathematical Model to Estimate the Transverse Shear Stress Distribution in a Rectangular Channel

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 596
Author(s):  
Babak Lashkar-Ara ◽  
Niloofar Kalantari ◽  
Zohreh Sheikh Khozani ◽  
Amir Mosavi
Keyword(s):  
Shear Stress ◽  
Stress Distribution ◽  
Fuzzy Inference ◽  
Rectangular Channel ◽  
Tsallis Entropy ◽  
Shear Stress Distribution ◽  
Data Series ◽  
Shear Stresses ◽  
Inference System ◽  
Aspect Ratios

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.

scholarly journals Wall Shear Stress Distribution of Small Aneurysms Prone to Rupture

Stroke ◽  
2014 ◽  
Vol 45 (1) ◽  
pp. 261-264 ◽  
Author(s):  
Vitor Mendes Pereira ◽  
Olivier Brina ◽  
Philippe Bijlenga ◽  
Pierre Bouillot ◽  
Ana Paula Narata ◽  
...  
Keyword(s):  
Shear Stress ◽  
Stress Distribution ◽  
Wall Shear Stress ◽  
Shear Stress Distribution ◽  
Wall Shear Stress Distribution ◽  
Wall Shear ◽  
Small Aneurysms
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