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<p>Two novel dimensionless design parameters, <i>C</i><sub>R-α</sub> and <i>C</i><sub>R-β</sub>, collectively known as the Coefficient of Refrigeration, <i>C</i><sub>R</sub>, are proposed for the performance evaluation of multi-stage vapor compression refrigeration systems. <i>C</i><sub>R</sub> consists of constitutive relations that incorporate the effects of operational variables (evaporation temperature, condensation temperature, and cooling duty) and system configuration (number of refrigeration stages) without any empirical coefficients. <i>C</i><sub>R</sub> strongly correlates with the total shaft work, with fitting indicators (<i>R</i><sup>2</sup> values) above 0.96. The simplified mathematical formulation of <i>C</i><sub>R</sub> eliminates the complex mathematical programming. Data validation confirms the robustness of the results, with errors below 0.2%. A new graphical approach, integrating <i>C</i><sub>R</sub> as the objective function, is proposed to optimize multi-stage vapor compression systems. The <i>C</i><sub>R</sub>-<i>H</i><sub>E</sub> plots identify the optimum cooling duty that delivers the minimum <i>C</i><sub>R</sub> value, thus providing a better visualization and monitoring of the optimization process. Case studies successfully demonstrate the contribution of <i>C</i><sub>R</sub> and the new graphical approach, delivering a total shaft work reduction of above 1% compared to the base designs.</p>

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The Generalized Coefficient of Refrigeration and New Graphical Approach for the Optimal Design of Multi-stage Vapor Compression Refrigeration Systems

  • 期刊论文

  • 发表日期：

    2025年11月28日

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  • Yoke Yi Chiah,
  • Shuhaimi bin Mahadzir

摘要

Two novel dimensionless design parameters, CR-α and CR-β, collectively known as the Coefficient of Refrigeration, CR, are proposed for the performance evaluation of multi-stage vapor compression refrigeration systems. CR consists of constitutive relations that incorporate the effects of operational variables (evaporation temperature, condensation temperature, and cooling duty) and system configuration (number of refrigeration stages) without any empirical coefficients. CR strongly correlates with the total shaft work, with fitting indicators (R2 values) above 0.96. The simplified mathematical formulation of CR eliminates the complex mathematical programming. Data validation confirms the robustness of the results, with errors below 0.2%. A new graphical approach, integrating CR as the objective function, is proposed to optimize multi-stage vapor compression systems. The CR-HE plots identify the optimum cooling duty that delivers the minimum CR value, thus providing a better visualization and monitoring of the optimization process. Case studies successfully demonstrate the contribution of CR and the new graphical approach, delivering a total shaft work reduction of above 1% compared to the base designs.