Modeling of the friction factor in pressure pipes using Bayesian Learning Neural Networks
The model proposed by Colebrook-White for calculating the coefficient of friction has been universally accepted by establishing an implicit transcendental function. This equation determines the friction coefficient for fully developed flows, that is, for turbulent flows with a Reynolds Number higher...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/15327
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ciencia_en_desarrollo/article/view/13241
https://repositorio.uptc.edu.co/handle/001/15327
- Palabra clave:
- Coeficiente fricción, Colebrook-White, Regularización Bayesiana, Red Neuronal Artificial
Artificial Neural Network, Bayesian Regularization, Coefficient of friction, Colebrook & White
- Rights
- License
- http://purl.org/coar/access_right/c_abf2