Dissertação
Estudo experimental do coeficiente de transferência de calor local por condensação do refrigerante R1234yf em um tubo horizontal liso com diâmetro interno de 4,8 mm
Fecha
2020-03-23Autor
Ramon de Paoli Mendes
Institución
Resumen
The aim of this work was the experimental determination of the condensation
heat transfer coefficient for the R1234yf fluid for mass velocities of 150 kg/(m².s), 200
kg/(m².s), 250 kg/(m².s) and 300 kg/(m².s), saturation temperatures of 30ºC and 35ºC
and qualitys steam of 10% to 90%. The experimental results were analyzed among
themselves and in relation to values made available by other researchers, revealing a
good harmony with these works. An increasing evolution of the heat transfer coefficient
was observed with the quality, which can be approximated by a third order polynomial
with an inflection point around the title of 50%. The results also indicated that the average heat transfer coefficient of R1234yf is lower than that of R134a of 28% and 9% for
the average mass velocities of 175 kg/(m².s) and 275 kg/(m².s), respectively. This result
was not affected by the two temperatures tested. Regarding the influence of mass speed
on the heat transfer coefficient of R1234yf, it was found that it increased by an average
of 20% for a variation of +100 kg(m².s) in mass speed for both the temperature of 30ºC
and to 35ºC. The condensation temperature did not have a direct influence on the coefficient with respect to the type of fluid or their mass velocity. However, the coefficient
decreases with increasing condensation temperature. In general, the coefficient was 7%
lower when the temperature went from 30 ºC to 35 ºC. Furthermore, the experimental
values of the condensation heat transfer coefficient were compared with theoretical results obtained from ten correlations in the literature. Among these, the Haragushi correlation proved to be the most suitable for estimating the heat transfer coefficient, despite
having a lower precision than that of a forecast model developed in the present work
based on the theory of neural networks, whose accuracy was 98%.