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Title: Free-convection condensation on single horizontal pin-fin tubes
Author: Ali, Hafiz-Muhummad
ISNI:       0000 0004 2709 5214
Awarding Body: Queen Mary, University of London
Current Institution: Queen Mary, University of London
Date of Award: 2011
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New experimental data are reported for free-convection condensation of ethylene glycol and R-113 on three-dimensional pin-fin tubes. Effects of pin geometry and tube thermal conductivity (for copper, brass and bronze giving a mean range of 400, 120 and 80 W/m K over the range of temperature of interest) were investigated. All tests were performed at near atmospheric pressure with downward flowing vapour at low velocity. Heat-transfer enhancement was found to be approximately twice the corresponding active surface area of the tubes, i.e. the surface area of the parts of the tube and pin surface not covered by condensate retained by surface tension. For ethylene glycol, the best performing pin-fin tube gave a heat-transfer enhancement of 5.8, about 24 % higher than the ‘equivalent’ two-dimensional integral-fin tube (i.e. with the same finroot diameter, longitudinal fin spacing and thickness and fin height). For R-113, the best enhancement was 5.9, about 10 % higher than the equivalent integral-fin tube. For both fluids tested, vapour-side, heat-transfer enhancement was found to increase with decreasing circumferential pin spacing and increasing pin height. Circumferential pin thickness had little effect on heat-transfer enhancement. Effects of tube thermal conductivity were found to be more significant for ethylene glycol than R-113. Retention angle measurements were made under static conditions (without condensation) and were found to be larger than for equivalent integral-fin tubes. An expression for condensate retention angle on pin-fin tubes was proposed and found to agree with the measured retention angles to ±15%. A semi-empirical model for condensation heat transfer on horizontal pin-fin tubes has been developed which accounts for the combined effect of gravity and surface tension. The model predicts the majority of available data to ±20 %.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Engineering