“…This shape change/deformation causes the bulk fluid to flow towards the bubble base region (Okawa et al 2005). The incoming liquid could lead to reduction in the temperature of the upstream superheated liquid layer at the bubble base (experimentally observed and reported in Cao et al (2016) and Sinha & Srivastava (2020a)). A similar reduction in the liquid temperature in the downstream base region is realized due to the vigorous mixing in the bubble wake area.…”
Section: Role Of Microlayer Evaporation Towards Bubble Growthmentioning
confidence: 92%
“…To elucidate on the various heat transfer mechanisms and to understand the role of the microlayer evaporation process, the experimentally obtained bubble growth curves of the present work have been compared with Mikic et al's (1970) bubble growth model. It is to be mentioned here that the growth curve from experimental data has been generated for T sup = 10 K (Ja = 30), which is the typical average wall superheat level observed for similar experimental conditions (Sinha & Srivastava 2020a). With reference to the model by Mikic et al (1970), for 0.1 < t + < 10, the bubble growth process is influenced by contributions from both inertial effects and thermal energy diffusion from the superheated fluid enveloping the vapour bubble; meanwhile, for t + 1 (t + > 10), inertial effects become negligible and the bubble growth process can be considered to be purely diffusion driven.…”
Section: Role Of Microlayer Evaporation Towards Bubble Growthmentioning
The phenomena of microlayer formation and its dynamic characteristics during the nucleate pool boiling regime have been widely investigated in the past. However, experimental works on real-time microlayer dynamics during nucleate flow boiling conditions are highly scarce. The present work is an attempt to address this lacuna and is concerned with developing a fundamental understanding of microlayer dynamics during the growth process of a single vapour bubble under nucleate flow boiling conditions. Boiling experiments have been conducted under subcooled conditions in a vertical rectangular channel with water as the working fluid. Thin-film interferometry combined with high-speed cinematography have been adopted to simultaneously capture the dynamic behaviour of the microlayer along with the bubble growth process. Transients associated with the microlayer have been recorded in the form of interferometric fringe patterns, which clearly reveal the evolution of the microlayer beneath the growing vapour bubble, the movement of the triple contact line and the growth of the dryspot region during the bubble growth process. While symmetric growth of the microlayer was confirmed in the early growth phase, the bulk flow-induced bubble deformation rendered asymmetry to its profile during the later stages of the bubble growth process. The recorded fringe patterns have been quantitatively analysed to obtain microlayer thickness profiles at different stages of the bubble growth process. For Re = 3600, the maximum thickness of the almost wedge-shaped microlayer was obtained as δ ~ 3.5 μm for a vapour bubble of diameter 1.6 mm. Similarly, for Re = 6000, a maximum microlayer thickness of δ ~ 2.5 μm was obtained for a bubble of diameter 1.1 mm.
“…This shape change/deformation causes the bulk fluid to flow towards the bubble base region (Okawa et al 2005). The incoming liquid could lead to reduction in the temperature of the upstream superheated liquid layer at the bubble base (experimentally observed and reported in Cao et al (2016) and Sinha & Srivastava (2020a)). A similar reduction in the liquid temperature in the downstream base region is realized due to the vigorous mixing in the bubble wake area.…”
Section: Role Of Microlayer Evaporation Towards Bubble Growthmentioning
confidence: 92%
“…To elucidate on the various heat transfer mechanisms and to understand the role of the microlayer evaporation process, the experimentally obtained bubble growth curves of the present work have been compared with Mikic et al's (1970) bubble growth model. It is to be mentioned here that the growth curve from experimental data has been generated for T sup = 10 K (Ja = 30), which is the typical average wall superheat level observed for similar experimental conditions (Sinha & Srivastava 2020a). With reference to the model by Mikic et al (1970), for 0.1 < t + < 10, the bubble growth process is influenced by contributions from both inertial effects and thermal energy diffusion from the superheated fluid enveloping the vapour bubble; meanwhile, for t + 1 (t + > 10), inertial effects become negligible and the bubble growth process can be considered to be purely diffusion driven.…”
Section: Role Of Microlayer Evaporation Towards Bubble Growthmentioning
The phenomena of microlayer formation and its dynamic characteristics during the nucleate pool boiling regime have been widely investigated in the past. However, experimental works on real-time microlayer dynamics during nucleate flow boiling conditions are highly scarce. The present work is an attempt to address this lacuna and is concerned with developing a fundamental understanding of microlayer dynamics during the growth process of a single vapour bubble under nucleate flow boiling conditions. Boiling experiments have been conducted under subcooled conditions in a vertical rectangular channel with water as the working fluid. Thin-film interferometry combined with high-speed cinematography have been adopted to simultaneously capture the dynamic behaviour of the microlayer along with the bubble growth process. Transients associated with the microlayer have been recorded in the form of interferometric fringe patterns, which clearly reveal the evolution of the microlayer beneath the growing vapour bubble, the movement of the triple contact line and the growth of the dryspot region during the bubble growth process. While symmetric growth of the microlayer was confirmed in the early growth phase, the bulk flow-induced bubble deformation rendered asymmetry to its profile during the later stages of the bubble growth process. The recorded fringe patterns have been quantitatively analysed to obtain microlayer thickness profiles at different stages of the bubble growth process. For Re = 3600, the maximum thickness of the almost wedge-shaped microlayer was obtained as δ ~ 3.5 μm for a vapour bubble of diameter 1.6 mm. Similarly, for Re = 6000, a maximum microlayer thickness of δ ~ 2.5 μm was obtained for a bubble of diameter 1.1 mm.
“…10 (b). On one hand, this type of bubble sliding is clearly beneficial to transferring cold working fluid to the heated wall, and promoting the mixing of hot working fluid near the heated wall and cold working fluid in the mainstream both of which are conducive to improving flow boiling heat transfer [51] . Fig.…”
“…Various methods, ranging from classic dye injection (Reynolds 1883) to particle image velocimetry (PIV) (Adrian 1991;Grant 1997), have been developed to visualize flows and gain insights into their behavior. The advent of high-speed imaging, coupled with the state-of-the-art computational resources, that allow huge data storage and fast processing speeds, have brought about a paradigm shift in flow visualization allowing for the capture of intricate dynamics of rapid phenomena, such as droplet impact, shockwaves and two-phase flows (Chen and Liang 2008;Thoroddsen et al 2018;Sinha and Srivastava 2020).…”
The interactions of an immiscible droplet impinging on liquid pools bear significant implications across a wide array of applications, as well as in natural phenomena. In this paper, the dynamics associated with an immiscible droplet impinging on a liquid pool/film of varying depths have been elucidated. The study encompasses the impact of silicone oil droplets of four different viscosities (1, 10, 100, and 1000 cSt) upon a water pool of three non-dimensional pool heights h* = 1, 2.5, and 5. The phenomenon of droplet impact at two Weber numbers (We = 50 and 100) is captured through high-speed videography. The dynamics of impingement, associated with the immiscible liquid combination, are delineated by employing Mask R-CNN machine learning (ML) model. ML model generated masks are used to ascertain the dynamics of various cavity parameter. Further insights into the phenomena have been developed through a detailed energy analysis carried out pre- and post-impact. The performance of ML model is compared with the manually annotated images, exhibiting impressive level of agreement. Results reveal that during the cavity formation phase, low viscosity droplets conform to the cavity shape during their descend into the pool. In contrast, high viscosity droplets maintain their shape during cavity formation, showing pinning at the oil-water interface. Energy analysis shows better energy transfer from droplet to the cavity for low viscosity droplets (> 90%), while less than 50% of the impact energy is transferred for higher viscosity droplets. This study is among the first to apply machine learning to this complex fluid phenomenon, offering insights into the physics and potential applications in multiphase flows.
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