Symbolic Regression-Based Genetic Approximations of the Colebrook Equation for Flow Friction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F18%3A10240152" target="_blank" >RIV/61989100:27740/18:10240152 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2073-4441/10/9/1175" target="_blank" >https://www.mdpi.com/2073-4441/10/9/1175</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/w10091175" target="_blank" >10.3390/w10091175</a>

Result language

angličtina

Original language name

Symbolic Regression-Based Genetic Approximations of the Colebrook Equation for Flow Friction

Original language description

Widely used in hydraulics, the Colebrook equation for flow friction relates implicitly to the input parameters; the Reynolds number, Re and the relative roughness of an inner pipe surface, epsilon/D with an unknown output parameter; the flow friction factor, ; = f (, Re, epsilon/D). In this paper, a few explicit approximations to the Colebrook equation; approximate to f (Re, epsilon/D), are generated using the ability of artificial intelligence to make inner patterns to connect input and output parameters in an explicit way not knowing their nature or the physical law that connects them, but only knowing raw numbers, {Re, epsilon/D}{}. The fact that the used genetic programming tool does not know the structure of the Colebrook equation, which is based on computationally expensive logarithmic law, is used to obtain a better structure of the approximations, which is less demanding for calculation but also enough accurate. All generated approximations have low computational cost because they contain a limited number of logarithmic forms used for normalization of input parameters or for acceleration, but they are also sufficiently accurate. The relative error regarding the friction factor , in in the best case is up to 0.13% with only two logarithmic forms used. As the second logarithm can be accurately approximated by the Pade approximation, practically the same error is obtained also using only one logarithm.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20302 - Applied mechanics

Project

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Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Water

ISSN

2073-4441

e-ISSN

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Volume of the periodical

10

Issue of the periodical within the volume

9

Country of publishing house

CH - SWITZERLAND

Number of pages

14

Pages from-to

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UT code for WoS article

000448821900067

EID of the result in the Scopus database

2-s2.0-85052812202