Experimental Study 0f Drag Reduction Phenomena in the Horizontal Tube with Nano SiO2 by Neural Network - Genetic Algorithm

Document Type : Research Article

Authors

1 Department of Chemical Engineering, Science and Research Branch, Islamic Azad University, Tehran, I.R. IRAN

2 Department of Chemical Engineering, South Tehran Branch, Islamic Azad University, Tehran, I.R. IRAN

Abstract

In this study, nano-silica oxide's effect as a Drag Reducing Agent (DRA) of water flow in a 12.7 and 25.4 mm galvanized pipe was investigated. The studied parameters include Nano silica oxide concentration, Flow rate, temperature,  and tube pipe diameter. To develop the conditions in preparing the Nano-particle on Drag Reduction (DR), nano-particles were provided in the top water-based fluid. To have a comprehensive analysis of process folding conditions, the experiments were carried out with three different drag-reducing concentration agents with three various temperatures and three different flow rates. Moreover, as a new method in this study, the experimental (Drag reduction percent) outputs were evaluated and analyzed using the Artificial neural network which is optimized by a genetic algorithm. In the consequence of algorithm genetic, the highest rate of drag reduction occurred at a horizontal pipeline 12.7 mm, temperature 41.07 °C, and a concentration of 0.628 with a 1441.84 flow rate was 25.84%.

Keywords

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References

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Iranian Journal of Chemistry and Chemical Engineering
Volume 40, Issue 4 - Serial Number 108
September and October 2021
Pages 1304-1314

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