Symbolic Regression-Based Genetic Approximations of the Colebrook Equation for Flow Friction
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Symbolic Regression-Based Genetic Approximations of the Colebrook Equation for Flow Friction
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Symbolic Regression-Based Genetic Approximations of the Colebrook Equation for Flow Friction
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20302 - Applied mechanics
Návaznosti výsledku
Projekt
—
Návaznosti
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Water
ISSN
2073-4441
e-ISSN
—
Svazek periodika
10
Číslo periodika v rámci svazku
9
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
14
Strana od-do
—
Kód UT WoS článku
000448821900067
EID výsledku v databázi Scopus
2-s2.0-85052812202