1. Enhancing the vertical downward condensation heat transfer of a plate heat exchanger by electrochemical etching.
- Author
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Nguyen, Dong Ho, Kim, TaeJoo, Kim, Jin Man, Kim, Taewan, Arkadumnuay, Thana, Mahian, Omid, Ahn, Ho Seon, and Wongwises, Somchai
- Subjects
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PLATE heat exchangers , *HEAT transfer coefficient , *HEAT transfer , *HEAT flux , *NUSSELT number , *CONDENSATION - Abstract
• Vertical downward condensation plate heat exchanger. • Electrochemical etching generates microscale roughness. • Enhance thermal-hydraulic performance of plate heat exchanger. • Analyze effect of heat flux, mass flux, vapor quality and surface roughness on heat transfer. • Multi-objective generic algorithm optimized designed roughness. • Pareto front solutions for maximizing performance. This research employed electrochemical etching to generate microscale roughness on a plate heat exchanger (PHE) thereby enhancing condensation heat transfer in a vertical downward flow. The effects of the mass flux, vapor quality, heat flux, saturation temperature and microscale surface roughness on the condensation heat transfer coefficient (HTC) and frictional pressure drop (FPD) of R-513a flowing through a PHE was experimentally investigated. Experimental measurements were made under various heat fluxes of 5–15 kW/m2, mass fluxes of 60–80 kg/m2s, saturation temperatures of 40–50 °C, and mean vapor qualities of 0.1–0.7. HTC increased by up to 28, 26, 74, and 32.5 % as the heat flux, mass flux, average quality, and microscale surface roughness were respectively increased, but decreased by 19 % with the saturation temperature. FPD increased as the mass flux and average vapor quality increased, whereas it was reduced as the refrigerant saturation temperature increased. In contrast, the heat flux had little to no influence on FPD. Correlations for predicting the Nusselt number and friction factor were postulated by considering influential dimensionless numbers during heat transfer. Maximizing the Nusselt number and thermal performance factor was ultimately resolved using a multi-objective genetic algorithm to find a Pareto front solution. Consequently, the optimal surface roughness was found to be 9.94 μm. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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