Modeling friction factor in pipeline flow using a GMDH-type neural network
The standard methods of calculating the fluid friction factor, the Colebrook–White and Haaland equations, require iterative solution of an implicit, transcendental function which entails high computational costs for large-scale piping networks while introducing as much as 15% error. This study appli...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2015-12-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2015.1056929 |