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Numerical Investigation on the Performance of Two-Throat Nozzle Ejectors with Different Mixing Chamber Structural Parameters

Author

Listed:
  • Fatong Jia

    (College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China)

  • Dazhang Yang

    (College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China)

  • Jing Xie

    (College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China
    National Experimental Teaching Demonstration Center for Food Science and Engineering, Shanghai 201306, China
    Shanghai Professional Technology Service Platform on Cold Chain Equipment Performance and Energy Saving Evaluation, Shanghai 201306, China)

Abstract

In this study, the effects of the mixing chamber diameter ( D m ), mixing chamber length ( L m ) and pre-mixing chamber converging angle ( θ pm ) were numerically investigated for a two-throat nozzle ejector to be utilized in a CO 2 refrigeration cycle. The developed simulated method was validated by actual experimental data of a CO 2 ejector in heat pump water heater system from the published literature. The main results revealed that the two-throat nozzle ejectors can obtain better performance with D m in the range of 8–9 mm, L m in the range of 64–82 mm and θ pm at approximately 60°, respectively. Deviation from its optimal value could lead to a poor operational performance. Therefore, the mixing chamber structural parameters should be designed at the scope around its optimal value to guarantee the two-throat nozzle ejector performance. The following research can be developed around the two-throat nozzle geometries to strengthen the ejector performance.

Suggested Citation

  • Fatong Jia & Dazhang Yang & Jing Xie, 2021. "Numerical Investigation on the Performance of Two-Throat Nozzle Ejectors with Different Mixing Chamber Structural Parameters," Energies, MDPI, vol. 14(21), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6900-:d:661295
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    References listed on IDEAS

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    Cited by:

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    2. Liu, Guangdi & Pu, Liang & Zhao, Hongxia & Chen, Zhuang & Li, Guangpeng, 2024. "Multi-objective optimization of CO2 ejector by combined significant variables recognition, ANN surrogate model and multi-objective genetic algorithm," Energy, Elsevier, vol. 295(C).

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