Published November 14, 2024 | Version Version 1
Dataset Open

Colebrook-White friction factor data

Creators

  • 1. ROR icon Shiraz University
  • 2. ROR icon CMCC Foundation - Euro-Mediterranean Center on Climate Change

Contributors

  • 1. ROR icon Shiraz University
  • 2. ROR icon CMCC Foundation - Euro-Mediterranean Center on Climate Change

Description

The Colebrook-White equation is a fundamental formula in fluid mechanics, widely used to determine the friction factor in turbulent flow through pipes. It is crucial for calculating head losses in pipelines and for the design and optimization of hydraulic systems. In this dataset, the friction factor (f) is obtained via numerical solution using the Newton-Raphson method, with a truncation accuracy of 1e-6.

The first and second columns of the provided dataset pertain to the Reynolds number (Re) and relative roughness (ε/D) variables, respectively. The data were generated across specified ranges [4500-2250000] with constant step of 4500 for Re and [0.00005, 0.0005, 0.005, 0.05, and 0.5] for ε/D. The third column presents  of the f values calculated using the Colebrook-White equation, which is given as:

 
1/(\sqrt(f)) = -2*log((\epsilon/D)/3.7 + 2.51/(Re*\sqrt(f)))
 
 
This dataset has multiple applications: it facilitates evaluating empirical formulas approximating the Colebrook-White equation and provides a valuable foundation for developing machine learning models to accurately predict the friction factor. Beyond aiding hydraulic system design, this dataset is a useful resource for researchers and engineers aiming to optimize pipeline flow, model turbulent pipe flow behavior, and advance computational methods in fluid dynamics.

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Additional details

Dates

Submitted
2024-11-14

References

  • Niazkar, M., Menapace, A., & Righetti, M. (2024, June). Estimating Colebrook-White Friction Factor Using Tree-Based Machine Learning Models. In International Symposium on Industrial Engineering and Automation (pp. 270-279). Cham: Springer Nature Switzerland.
  • Niazkar, M. (2019). Revisiting the estimation of Colebrook friction factor: a comparison between artificial intelligence models and CW based explicit equations. KSCE J Civ Eng. 2019; 23 (10): 4311–26.