Determination of the Inside Diameter of Pressure Pipes for Drinking Water Systems Using Artificial Neural Networks

The fifth-degree polynomial equation determines the diameter in pressurized drinking water systems. The input variables are Q: flow (m3/s), H: pressure drop (m); L: pipe length (m); ε: roughness (m), ϑ: kinematic viscosity (m2/s), and Ʃk: sum of minor loss coefficients (dimensionless). After applyin...

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Autores:
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
eng
OAI Identifier:
oai:repositorio.uptc.edu.co:001/14335
Acceso en línea:
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/14037
https://repositorio.uptc.edu.co/handle/001/14335
Palabra clave:
Artificial Neural Network
cold chain.
Darcy-Weisbach
Levenberg-Marquardt
pipeline hydraulics
Colebrook-White
Darcy-Weisbach
hidráulica de tuberías
Levenberg-Marquardt
red neuronal artificial
Rights
License
http://creativecommons.org/licenses/by/4.0