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Experimental study on diffusion absorption refrigeration systems with low GWP refrigerants

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  • Kim, Gahyeong
  • Choi, Hyung Won
  • Lee, Gawon
  • Lee, Jang Seok
  • Kang, Yong Tae

Abstract

The diffusion absorption refrigeration (DAR) cycle is driven by heat input. The DAR systems do not employ pumps or compressors; they use refrigerants, absorbents, and auxiliary gases as working fluids. In this study, experiments were conducted on refrigerants with low GWP. The refrigerants R1234ze(E) and R600a (a natural refrigerant) were used in the DAR cycles with dimethylacetamide (DMAC) and isooctane as the absorbents, respectively. To investigate the operating characteristics of refrigerants with low GWP in the DAR cycle, the evaporation temperature and generator outlet temperature of the cycle were analyzed against the concentration of the working fluid and its charge pressure. In addition, the performance of the cycle was evaluated by the bubble pump shape. Using the results, the relationship between the shape of the bubble pump and the performance of the DAR cycle was analyzed. The maximum coefficient of performance of DAR achieved using R600a/isooctane was estimated as 0.157with the tube diameter of 3.17 mm and that of R1234ze(E)/DMAC DAR was estimated as 0.134 with the tube diameter of 4.76 mm.

Suggested Citation

  • Kim, Gahyeong & Choi, Hyung Won & Lee, Gawon & Lee, Jang Seok & Kang, Yong Tae, 2020. "Experimental study on diffusion absorption refrigeration systems with low GWP refrigerants," Energy, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:energy:v:201:y:2020:i:c:s0360544220307337
    DOI: 10.1016/j.energy.2020.117626
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    References listed on IDEAS

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    1. Taieb, Ahmed & Mejbri, Khalifa & Bellagi, Ahmed, 2016. "Detailed thermodynamic analysis of a diffusion-absorption refrigeration cycle," Energy, Elsevier, vol. 115(P1), pages 418-434.
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    Cited by:

    1. Noushabadi, Abolfazl Sajadi & Lay, Ebrahim Nemati & Dashti, Amir & Mohammadi, Amir H. & Chofreh, Abdoulmohammad Gholamzadeh & Goni, Feybi Ariani & Klemeš, Jiří Jaromír, 2023. "Insights into modelling and evaluation of thermodynamic and transport properties of refrigerants using machine-learning methods," Energy, Elsevier, vol. 262(PA).
    2. Lee, Gawon & Choi, Hyung Won & Kang, Yong Tae, 2021. "Cycle performance analysis and experimental validation of a novel diffusion absorption refrigeration system using R600a/n-octane," Energy, Elsevier, vol. 217(C).

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