Discharge estimation for trapezoidal open channels applying fuzzy transformation method to a flow equation
The aim of this paper is to implement fuzzy logic theory in order to estimate the discharge for open channels, which is a well-known physical problem affected by many factors. The problem can be solved by the Manning equation but the parameters present uncertainties as to their true-real values. Esp...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IWA Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/29b442f9a0834eb99c7d3768f39315e0 |
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| Sumario: | The aim of this paper is to implement fuzzy logic theory in order to estimate the discharge for open channels, which is a well-known physical problem affected by many factors. The problem can be solved by the Manning equation but the parameters present uncertainties as to their true-real values. Especially, the Manning n roughness coefficient, which is an empirically derived coefficient, presents quite a high variation for different substrates. With the help of fuzzy logic and utilizing a fuzzy transformation method, it is possible to include the uncertainties of the problem in the calculation process. In this case, it is feasible to estimate the discharge, putting more emphasis on different uncertainty rates of the Manning roughness coefficient, while the rest of the parameters remain with constant or zero uncertainty level. By taking different α-cut levels, it is shown that the methodology gives realistic and reliable results, presenting with great accuracy the variations of the water discharge for trapezoidal open channels. In this way, a possible underestimation or overestimation of the actual physical condition is avoided, by helping engineers and researchers to obtain a more comprehensive view of the real physical conditions, and thus make better management plans. Highlights
Novel use of fuzzy logic in the Manning equation.;
A new approach to estimate the discharge in open natural channels.;
Includes Manning's roughness coefficient uncertainties in the calculation process.;
Comparison between the uncertainty parameters of the Manning equation.;
Provides accurate information for better management plans and decisions.; |
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