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CFD Simulation and Experimental Study of Working Process of Screw Refrigeration Compressor with R134a

Author

Listed:
  • Huagen Wu

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Hao Huang

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    State Key Laboratory of Compressor Technology, Hefei 230001, China)

  • Beiyu Zhang

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Baoshun Xiong

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Kanlong Lin

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

Twin-screw refrigeration compressors have been widely used in many industry applications due to their unique advantages. The performance of twin-screw refrigeration compressors is generally predicted by one-dimensional numerical simulation or empirical methods; however, the above methods cannot obtain the distribution of the fluid pressure field and temperature field inside the compressor. In this paper, a three-dimensional model was established based on the experimental twin-screw refrigeration compressor. The internal flow field of the twin-screw compressor was simulated by computational fluid dynamics (CFD) software using structured dynamic grid technology. The flow and thermodynamic characteristics of the fluid inside the compressor were analyzed. The distribution of the internal pressure field, temperature field, and velocity field in the compressor were obtained. Comparing the P-θ indicator diagram and the performance parameters of the compressor with the experimental results, it was found that the results of the three-dimensional numerical simulation were consistent with the experimental data. The maximum error was up to 2.578% on the adiabatic efficiency at the partial load working condition. The accuracy of the 3D numerical simulation of the screw compressors was validated and a new method for predicting the performance of twin-screw refrigeration compressors was presented that will be helpful in their design.

Suggested Citation

  • Huagen Wu & Hao Huang & Beiyu Zhang & Baoshun Xiong & Kanlong Lin, 2019. "CFD Simulation and Experimental Study of Working Process of Screw Refrigeration Compressor with R134a," Energies, MDPI, vol. 12(11), pages 1-14, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2054-:d:235258
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    References listed on IDEAS

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    1. Sun-Seok Byeon & Jae-Young Lee & Youn-Jea Kim, 2017. "Performance Characteristics of a 4 × 6 Oil-Free Twin-Screw Compressor," Energies, MDPI, vol. 10(7), pages 1-16, July.
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    Cited by:

    1. Chia-Cheng Tsao & Wen-Kai Lin & Kai-Yuan Lai & Savas Yavuzkurt & Yao-Hsien Liu, 2023. "Numerical Investigation of Compression and Expansion Process of Twin-Screw Machine Using R-134a," Energies, MDPI, vol. 16(8), pages 1-14, April.
    2. Shizhong Sun & Yiwei Feng & Ziwen Xing & Minglong Zhou & Wenqing Chen & Chuang Wang & Hanyang Cui, 2022. "Study on Influential Mechanism of Trailing Edge Sweep Angle on Aerodynamic Noise of a Centrifugal Air Compressor," Energies, MDPI, vol. 15(19), pages 1-14, October.
    3. Tao Wang & Qiang Qi & Wei Zhang & Dengyi Zhan, 2023. "Research on Optimization of Profile Parameters in Screw Compressor Based on BP Neural Network and Genetic Algorithm," Energies, MDPI, vol. 16(9), pages 1-17, April.

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    1. Tao Wang & Qiang Qi & Wei Zhang & Dengyi Zhan, 2023. "Research on Optimization of Profile Parameters in Screw Compressor Based on BP Neural Network and Genetic Algorithm," Energies, MDPI, vol. 16(9), pages 1-17, April.
    2. Zhilong He & Tao Wang & Xiaolin Wang & Xueyuan Peng & Ziwen Xing, 2018. "Experimental Investigation into the Effect of Oil Injection on the Performance of a Variable Speed Twin-Screw Compressor," Energies, MDPI, vol. 11(6), pages 1-14, May.

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