Research Article
Evaluation Optimal Friction Factor Correlation in Turbulent Pipe Flow by Genetic Algorithm
@INPROCEEDINGS{10.4108/eai.28-6-2020.2297927, author={Qais Yousif and Omar Alomar and Ibrahim Mohamed and Majid Najm}, title={Evaluation Optimal Friction Factor Correlation in Turbulent Pipe Flow by Genetic Algorithm }, proceedings={Proceedings of the 1st International Multi-Disciplinary Conference Theme: Sustainable Development and Smart Planning, IMDC-SDSP 2020, Cyperspace, 28-30 June 2020}, publisher={EAI}, proceedings_a={IMDC-SDSP}, year={2020}, month={9}, keywords={colebrook equation friction factor genetic algorithms}, doi={10.4108/eai.28-6-2020.2297927} }- Qais Yousif
Omar Alomar
Ibrahim Mohamed
Majid Najm
Year: 2020
Evaluation Optimal Friction Factor Correlation in Turbulent Pipe Flow by Genetic Algorithm
IMDC-SDSP
EAI
DOI: 10.4108/eai.28-6-2020.2297927
Abstract
. The prediction accuracies of friction factor correlations in turbulent pipe flow have remained unsatisfactory due to Colebrook equation is characterized as an implicit correlation. Thus, this works deals with numerical simulation for optimization the correlation of friction factor (fD) in turbulent pipe flow. Genetic Algorithms (GAs) method has been used to evaluate the accuracy of six most used explicit models as an alternative to the Colebrook equation. The fD has been estimated for higher ranges of Reynolds Number (Re) and the relative roughness of pipe (ε⁄D). The evaluation process has been implemented through comparing the percentage of differences between the values of fD obtained using those correlations with that obtained using Colebrook equation. The optimized results clearly show that the Model-1 and Model-5 provide the lowest percentage of difference as compared to the other explicit models. Results indicated that GAs has succeeded in reducing the computational time by eliminating the iterative process.
