Optimization of Vapor-Compression System for Local Cooling

This study presents a multi-objective thermodynamic optimization of an integrated vapor-compression cooling architecture designed for localized thermal regulation under constrained operating conditions. Evaporator flow rate, condenser flow rate, capillary tube length, and copper pipe geometry were systematically analyzed using Response Surface Methodology (RSM) coupled with Central Composite Design. Sixty experiments were conducted to construct second-order predictive models for temperature difference (ΔT) and coefficient of performance (COP), validated through ANOVA and residual diagnostics. Statistical analysis identified capillary tube length as the dominant parameter (p < 0.001), with significant interaction effects between geometric and operational variables. Optimization using the D-optimality criterion yielded ΔT = 2.593°C and COP = 1.999 at optimal conditions. Experimental uncertainty remained below 5%, confirming model robustness. The proposed framework establishes a scalable and statistically rigorous methodology for compact refrigeration cycle optimization and advanced localized thermo-fluid system design.

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Publication Details

Journal
Journal of Engineering Research
Published
2026-05-01
DOI
https://doi.org/10.1016/j.jer.2026.04.022
Primary Topic
Heat Transfer Mechanisms
Type
article
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article

Optimization of Vapor-Compression System for Local Cooling

Nesrin Adıgüzel, Mehmet Aksoy, Musa DEMİR, Ahmet Numan Özakın
Journal of Engineering Research
Heat Transfer Mechanisms
article

Optimization of Vapor-Compression System for Local Cooling

Nesrin Adıgüzel, Mehmet Aksoy, Musa DEMİR, Ahmet Numan Özakın
article en

Abstract

This study presents a multi-objective thermodynamic optimization of an integrated vapor-compression cooling architecture designed for localized thermal regulation under constrained operating conditions. Evaporator flow rate, condenser flow rate, capillary tube length, and copper pipe geometry were systematically analyzed using Response Surface Methodology (RSM) coupled with Central Composite Design. Sixty experiments were conducted to construct second-order predictive models for temperature difference (ΔT) and coefficient of performance (COP), validated through ANOVA and residual diagnostics. Statistical analysis identified capillary tube length as the dominant parameter (p < 0.001), with significant interaction effects between geometric and operational variables. Optimization using the D-optimality criterion yielded ΔT = 2.593°C and COP = 1.999 at optimal conditions. Experimental uncertainty remained below 5%, confirming model robustness. The proposed framework establishes a scalable and statistically rigorous methodology for compact refrigeration cycle optimization and advanced localized thermo-fluid system design.

Journal of Engineering Research
Giresun University (TR), Atatürk University (TR)
Affordable and clean energy
Openalex Percentile: Top 10%
Heat Transfer Mechanisms
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