Comment on “Gene expression programming analysis of implicit Colebrook–White equation in turbulent flow friction factor calculation”

2014 ◽  
Vol 124 ◽  
pp. 402-405 ◽  
Author(s):  
Ali R. Vatankhah
Keyword(s):  
Gene Expression ◽  
Turbulent Flow ◽  
Friction Factor ◽  
Gene Expression Programming ◽  
Flow Friction ◽  
Programming Analysis

scholarly journals Discussion of “Gene expression programming analysis of implicit Colebrook–White equation in turbulent flow friction factor calculation” by Saeed Samadianfard [J. Pet. Sci. Eng. 92-93 (2012), 48-55]

2017 ◽  
Author(s):  
Dejan Brkić ◽  
Brkic Dejan
Keyword(s):  
Gene Expression ◽  
Turbulent Flow ◽  
Friction Factor ◽  
Relative Error ◽  
Energy Security ◽  
Gene Expression Programming ◽  
Security Systems ◽  
Flow Friction ◽  
Programming Analysis ◽  
Maximal Relative Error

Maximal relative error of the explicit approximation to the Colebrook equation for flow friction presented in the discussed paper by Saeed Samadianfard [J. Pet. Sci. Eng. 92-93 (2012), 48-55; doi. 10.1016/j.petrol.2012.06.005] is investigated. Samadianfard claims that his approximation is very accurate with the maximal relative error of no more than 0.08152%. Here is shown that this error is about 7%. Related comments about the paper are also enclosed. ; JRC.F.3-Energy Security, Systems and Market

Estimation of the Darcy–Weisbach friction factor for ungauged streams using Gene Expression Programming and Extreme Learning Machines

2019 ◽  
Vol 568 ◽  
pp. 311-321 ◽  
Author(s):  
Heather Anne Milukow ◽  
Andrew D. Binns ◽  
Jan Adamowski ◽  
Hossein Bonakdari ◽  
Bahram Gharabaghi
Keyword(s):  
Gene Expression ◽  
Friction Factor ◽  
Gene Expression Programming ◽  
Extreme Learning Machines ◽  
Learning Machines
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