Review of new flow friction equations: Constructing Colebrook explicit correlations accurately
| Autor: | Pavel Praks, Dejan Brkić |
|---|---|
| Přispěvatelé: | University of Niš, IRC, IES, Ispra, Italy, affiliation inconnue, IT4Innovations - National Supercomputing Center [Ostrava], Technical University of Ostrava [Ostrava] (VSB) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Engineering
Civil hydraulic flow friction 0208 environmental biotechnology Engineering Multidisciplinary Computational intelligence 02 engineering and technology Wright Omega function Computer Science Artificial Intelligence [SPI]Engineering Sciences [physics] 0203 mechanical engineering Approximation error computational intelligence Feature (machine learning) Darcy friction factor formulae FOS: Mathematics Applied mathematics Colebrook equation Engineering Geological Engineering Ocean Mathematics - Numerical Analysis [MATH]Mathematics [math] MATLAB Engineering Aerospace Mathematics computer.programming_language Applied Mathematics General Engineering Numerical Analysis (math.NA) dissemin Engineering Marine 020801 environmental engineering Engineering Mechanical Engineering Manufacturing 020303 mechanical engineering & transports Flow (mathematics) explicit approximations Engineering Industrial Mathematical & Computational Biology Asymptotic expansion Symbolic regression symbolic regression computer Wright omega-function |
| Zdroj: | Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, 2020, 36, ⟨10.23967/j.rimni.2020.09.001⟩ |
| DOI: | 10.23967/j.rimni.2020.09.001⟩ |
| Popis: | International audience; Using only a limited number of computationally expensive functions, we show a way how to construct accurate and computationally efficient approximations of the Colebrook equation for flow friction based on the asymptotic series expansion of the Wright ω-function and on symbolic regression. The results are verified with 8 million of Quasi-Monte Carlo points covering the domain of interest for engineers. In comparison with the built-in “wrightOmega” feature of Matlab R2016a, the herein introduced related approximations of the Wright ω-function significantly accelerate the explicit solution of the Colebrook equation. Such balance between speed and accuracy could be achieved only using symbolic regression, a computational intelligence approach that can find optimal coefficients and the best structure of the equation. The presented numerical experiments show that the novel symbolic regression approximation reduced the maximal relative error from 0.045% to 0.00337%, i.e. more than 13 times, even the complexity remains almost unchanged. Moreover, we also provide a novel highly precise symbolic regression approximation (max. relative error 0.000024%), which, for the same speed as asymptotic expansion, reduces the relative error by factor 219. This research is motivated by estimation of flow rate using electrical parameters of pumps where direct measurement is not always possible such as in offshore underwater pipelines. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|