An official website of the United States government
Abstract Undesired heat transfer during droplet impact on cold surfaces can lead to ice formation and damage to renewable infrastructure, among others. To address this, superhydrophobic surfaces aim to minimize the droplet surface interaction thereby, holding promise to greatly limit heat transfer. However, the droplet impact on such surfaces spans only a few milliseconds making it difficult to quantify the heat exchange at the droplet–solid interface. Here, we employ high‐speed infrared thermography and a three‐dimensional transient heat conduction COMSOL model to map the dynamic heat flux distribution during droplet impact on a cold superhydrophobic surface. The comprehensive droplet impact experiments for varying surface temperature, droplet size, and impacting height reveal that the heat transfer effectiveness () scales with the dimensionless maximum spreading radius as , deviating from previous semi‐infinite scaling. Interestingly, despite shorter contact times, droplets impacting from higher heights demonstrate increased heat transfer effectiveness due to expanded contact area. The results suggest that reducing droplet spreading time, as opposed to contact time alone, can be a more effective strategy for minimizing heat transfer. The results presented here highlight the importance of both contact area and contact time on the heat exchange between a droplet and a cold superhydrophobic surface.
more »
« less
Heat transfer and phase interface dynamics during impact and evaporation of subcooled impinging droplets on a heated surface
A comprehensive understanding of heat transfer mechanisms and hydrodynamics during droplet impingement on a heated surface and subsequent evaporation is crucial for improving heat transfer models, optimizing surface engineering, and maximizing overall effectiveness. This work showcases findings related to heat transfer mechanisms and simultaneous tracking of the moving contact line (MCL) for subcooled impinging droplets across a range of surface temperatures, utilizing a custom MEMS device, at multiple impact velocities. Experimental results show that heat flux caused by droplet impingement has a weaker dependence on surface temperature than receding MCL heat transfer due to evaporation, which is significantly surface temperature dependent. The measurements also demonstrate that when a droplet impacts a heated surface and evaporates, the process can be divided into two segments based on the effective heat transfer rate: an initial conduction-dominated segment followed by another segment dominated by surface evaporation. For subcooled impinging droplets, the effect of oscillatory motion is found to be negligible, unlike in a superheated regime; hence, heat conduction into the droplet entirely governs the first segment. Results also show that heat flux at the solid-liquid interface of an impinging droplet increases with the rise of either impact velocity or surface temperature. In the subcooled regime, droplets impacting a heated surface have approximately 1.6 times higher vertical heat flux values than gently deposited droplets. Furthermore, this study quantifies the contributions of buoyancy and thermocapillary convection within the droplet to the overall heat transfer.
more »
« less
- Award ID(s):
- 1846165
- PAR ID:
- 10500568
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Applied Thermal Engineering
- Volume:
- 248
- Issue:
- PA
- ISSN:
- 1359-4311
- Page Range / eLocation ID:
- 123152
- Subject(s) / Keyword(s):
- Droplet impingement Droplet evaporation Moving contact line Phase-change heat transfer MEMS device
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
ABSTRACT At low surface superheat levels, water droplets deposited on ZnO nanostructured surfaces vaporize primarily by conduction transport of heat from the solid heated surface to the liquid-vapor interface. As the superheat is increased beyond the onset of bub- ble nucleation threshold (ONB), an increasing number of active nucleation sites are observed within the evaporating droplet re- ducing the time required to completely evaporate the droplet. There were two primary objectives of this investigation; first, to determine how system parameters dictate when ONB occurs and how its heat transfer enhancement effect increases with superheat. The second was to develop a physics-inspired model equation for the evaporation time of a droplet on a nanostructured surface which accounts for effects of conduction transport in the liquid layer of the droplet and nucleate boiling. A shape factor model for conduction-dominated vaporiza- tion of the droplet was first constructed. A correction factor was introduced to account for deviation of the measured droplet evaporation times from the conduction-dominated model. The correction factor form was postulated using a modified form of the onset of nucleate boiling parameter used in the well-known model analysis developed by Hsu to predict onset of nucleation and active nucleation site range in a thermal boundary layer as- sociated with forced convection boiling. Droplet footprint radii were experimentally observed to be affected by superheat and an additional term was introduced to account for this phenomenon. A term was also introduced to include correlations for boiling to incorporate system properties. This modeling led to an evaporation time equation contain- ing numerical constants dictated by the idealizations from the physical modeling. To develop an improved empirical model equation, these numerical values were taken to be adjustable constants, and a genetic algorithm was used to determine the ad- justable constant values that best fit a data collection spanning wide variations of droplet size, surface apparent contact angle, and superheat level. The best-fit constants match the data to an absolute fractional error of 26%. The model equation developed in this study provides insight into the interaction between con- duction transport and nucleate boiling effects that can arise in droplet vaporization processes.more » « less
-
Planar Laser Induced Fluorescence (PLIF) has been demonstrated to investigate a round jet impinging on a flat surface. Detailed thermal field distributions have been obtained near the flat target surface to characterize the wall jet development ensuing from the stagnation point. While PLIF has been demonstrated for combustion applications to measure concentration gradients within a mixture, its application for temperature field measurements is less established. Therefore, the technique was applied to a simple, cylindrical impinging jet. The jet Reynolds number varied with Rejet = 5,000 – 15,000 while the jet – to – target surface spacing varied from H / D = 4 – 10. The cooling jet (Tjet ~ 300 K) impinged on a flat, heated surface. The PLIF technique was able to capture the free jet structure and jet development along the target surface. With a short impingement length (H / D = 4), the potential core of the jet strikes the target surface. The thermal gradients captured during the experiments demonstrate the fully turbulent nature of the impinging jet with H / D = 10. The thermal boundary development along the target surface is clearly captured using this fluorescence method. The near wall temperature gradients acquired with the PLIF method have been used to calculate heat transfer coefficients on the heated surface, and these values compare favorably to those measured using a well-established steady state, heat transfer method. The PLIF technique has been demonstrated for this fundamental impingement setup, and it has proven to be applicable to more complex heat transfer and cooling applications.more » « less
-
ABSTRACT For droplet vaporization on a superheated hydrophilic surface, earlier studies have demonstrated that use of machine learning tools to analyze both image information from high-speed video and digital data from sensors can be an effective path to understanding the physics and developing a useful model to predict performance when the surface superheat is at low to moderate levels. For such conditions, the two-phase morphology of the system is usually well-behaved, exhibiting conduction-dominated film evaporation of the spread droplet, or nucleate boiling at active nucleation sites in the liquid film of the spread droplet. At higher surface superheat levels, experiments have shown that the droplet vaporization process becomes chaotic, with the process alternating between rapid vaporization of liquid in contact with the surface and ejection of liquid off the surface by strong vapor recoil forces. For our experiments with water droplets at atmospheric pressure, this regime corresponds to superheat levels ranging from about 35 to 55 deg. C. At the low superheat end of this regime, extremely high mean heat flux levels are achieved, but as superheat further increases, less of the surface stays wetted due to the increasing vapor recoil forces, and heat flux begins to decrease as the boiling process becomes like transition pool boiling with progressively less of the surface in contact with liquid. This exploration of the use of a specialized convolution neural network (CNN) to simultaneously analyze high speed video images and digital data for this high-superheat, near-critical-heat-flux regime of droplet vaporization is of special interest for two reasons. First, this vaporization regime results in high heat flux levels that make it attractive for high heat flux cooling for high-powered electronics. Use of machine learning tools to learn more about the mechanisms of this vaporization regime may open the door to new high flux thermal management technologies. In addition, because of its complexity, the two-phase morphology of the vaporization process in this regime is expected to be a very challenging task for CNN machine learning tools. In this study we conducted deposited water droplet spreading and vaporization experiments that captured digital data input (measured surface superheat, mean heat flux during the vaporization process, wetting contact angle, droplet size, etc.) and images of the droplet vaporization two-phase morphology from high-speed video during each experiment. This paper summarizes our successful development of a specialized hybrid CNN design that is trained using the combination of digital measurements and images obtained in our experiments. This CNN design provides deep insight into correlation between the two-phase morphology and heat transfer performance for this near critical heat flux vaporization regime. It also provides a pathway to a heat transfer performance model that fits the performance data to a high level of agreement. Using data collected from the droplet deposition experiment, this network design has been trained to predict the mean heat flux with a root mean square percent error of only about 2.0% and 8.0% on a training and testing dataset respectively. The hybrid network developed in this research appears to be a promising strategy for analyzing experimental data for physical systems with complex morphology that are best investigated experimentally with a combined use of imaging and digital sensor instrumentation.more » « less
-
Abstract Jet impingement can be particularly effective for removing high heat fluxes from local hotspots. Two-phase jet impingement cooling combines the advantage of both the nucleate boiling heat transfer with the single-phase sensible cooling. This study investigates two-phase submerged jet impingement cooling of local hotspots generated by a diode laser in a 100 nm thick Hafnium (Hf) thin-film on glass. The jet/nozzle diameter is ∼1.2 mm and the normal distance between the nozzle outlet and the heated surface is ∼3.2 mm. Novec 7100 is used as the coolant and the Reynolds numbers at the jet nozzle outlet range from 250 to 5000. The hotspot area is ∼ 0.06 mm2 and the applied hotspot-to-jet heat flux ranges from 20 W/cm2 to 220 W/cm2. This heat flux range facilitates studies of both the single-phase and two-phase heat transport mechanisms for heat fluxes up to critical heat flux (CHF). The temporal evolution of the temperature distribution of the laser heated surface is measured using infrared (IR) thermometry. This study also investigates the nucleate boiling regime as a function of the distance between the hotspot center and the jet stagnation point. For example, when the hotspot center and the jet are co-aligned (x/D = 0), the CHF is found to be ∼ 177 W/cm2 at Re ∼ 5000 with a corresponding heat transfer coefficient of ∼58 kW/m2.K. While the CHF is ∼ 130 W/cm2 at Re ∼ 5000 with a jet-to-hotspot offset of x/D ≈ 4.2.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.applthermaleng.2024.123152
