Optimization Of Hydrocarbon Ejector Using Computational Fluid Dynamics

Authors

DOI:

https://doi.org/10.4186/ej.2022.26.5.1 Full article

Abstract

Ejector is a powerful emerging thermo-compressor, which is more effective when used with hydrocarbon refrigerants because of its unique thermophysical properties. Therefore, in the present work, a steam ejector model is designed and validated with experimental results to evaluate its accuracy, followed by a detailed comparative study of hydrocarbons and synthetic refrigerants namely pentane, propane, butane, iso-butane, R1234-ze and R1234-yf by computational fluid dynamics and literature Review. The effectiveness of both classes of refrigerants is measured through entrainment ratio, critical backpressure, and thermophysical properties (Literature Review). Pentane was selected as a working fluid since it has comparatively high combination of entrainment ratio and critical back pressure with refrigeration compatible properties. Lastly, the optimized geometry was simulated by varying diameter of constant area zone, nozzle exit position and nozzle expansion angle through Computational Fluid dynamics. The simulation results provide insight into shockwaves, boundary layer separation, vortex formation of ejector flow.

Keywords:

COP, critical backpressure, entrainment ratio, hydrocarbon refrigerants

Affiliations

  • Muhammad Hadi NED University of Engineering & Technology
  • Ahsan Arshad NED University of Engineering & Technology
  • Nagoor Basha Shaik Chulalongkorn University
  • Watit Benjapolakul Chulalongkorn University
  • Qandeel Fatima Gillani COMSATS University

Corresponding author: Nagoor Basha Shaik, nagoor.s@chula.ac.th

2221 1443

Author Biographies

  • Chemical Engineering Department, NED University of Engineering & Technology, Karachi, Pakistan

  • Chemical Engineering Department, NED University of Engineering & Technology, Karachi, Pakistan

  • Artificial Intelligence, Machine Learning, and Smart Grid Technology Research Unit, Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

  • Artificial Intelligence, Machine Learning, and Smart Grid Technology Research Unit, Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand

  • Department of Civil Engineering, COMSATS University, Islamabad, Abbottabad Campus, Abbottabad 22010, Khyber Pakhtunkhwa, Pakistan

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How to Cite

[1]
M. Hadi, A. Arshad, N. B. Shaik, W. Benjapolakul, and Q. F. Gillani, “Optimization Of Hydrocarbon Ejector Using Computational Fluid Dynamics”, Eng. J., vol. 26, no. 5, pp. 1–11, May 2022, doi: 10.4186/ej.2022.26.5.1.

Citations

Published

2022-05-31

Issue

Section

Environment, Energy and Natural Resources