The diminishment of specific heat and surface tension of coolant droplet in a dropwise evaporation process: A novel methodology to enhance the heat transfer rate. Issue 4 (4th July 2018)

• Record Type: Journal Article
• Authors: Bhatt, N. H.; Pati, A. R.; Das, Lily; Panda, A.; Varshney, P; Kumar, A.; Munshi, B.; Mohapatra, S. S.
• Is Part Of: Experimental heat transfer. Volume 31:Issue 4(2018)
• Page Start: 355
• Page End: 372
• Publication Date: 2018-07-04
• Subjects: Fast cooling -- quenching -- evaporative cooling -- recoiling -- latent heat extraction; Heat -- Transmission -- Measurement -- Periodicals; 621.4022
• DOI: 10.1080/08916152.2017.1419314
• Languages: English
• ISSNs: 0891-6152

Abstract

ABSTRACT: The rate of dropwise evaporation is significantly altered by additives, such as benzene, n-hexane and acetone in water. These additives change some of the thermal and physical properties of the coolants, which have significant impact on various parameters that controls the droplet evaporative cooling, such as sensible, heat extraction period, droplet momentum and contact area. The open literature does not reveal the effects of the aforesaid additives on the dropwise evaporation. Therefore, in the current work, an attempt has been made to investigate the effects of above-mentioned additives on dropwise evaporation rate and reveal the mechanism involved. The droplet evaporative cooling experiments are conducted on a 2 mm thick AISI 304 steel plate (10 × 10 mm). The result shows that with increment in benzene and n-hexane concentration in water, the evaporation time significantly reduces. This is attributed to the decreasing surface tension, specific heat and contact angle. However, in case of acetone, the reduction in evaporation time is achieved only up to a concentration of 300 ppm, beyond which the evaporation time increases. This is because of the significant consumption of time in recoiling of the droplet. In addition to the above, the mechanism for the aforesaid enhancement process is tried to reveal by developing the models. For the validation of the developed equations, experimental results are compared with the numerically computed data. The comparison discloses that the developed model is quite accurate and shows insignificant variation from the experimental results. R 2 and RMSE are also calculated for both the developed models and based on minimum recommended RMSE; the best model is also suggested.