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Simulation and experiment on supercooled sessile water droplet freezing with special attention to supercooling and volume expansion effects
International Journal of Heat and Mass Transfer ( IF 5.0 ) Pub Date : 2018-12-01 , DOI: 10.1016/j.ijheatmasstransfer.2018.07.021
Xuan Zhang , Xin Liu , Xiaomin Wu , Jingchun Min

Abstract The freezing process of supercooled water droplets on cold plates is studied experimentally and numerically. A numerical model that considers both the supercooling effect on the physical properties and the volume expansion effect on the droplet freezing profile is established to simulate the droplet freezing behaviors using the Solidification/Melting model. Experiments are conducted on both hydrophilic and hydrophobic surfaces for 5, 10, 20, 30 and 40 μL supercooled water droplets. The droplet freezing behaviors including the freezing front movement and freezing time are observed using the image recognition technology. The evolution of the freezing front calculated by the numerical model agrees better with the experimental observation than the traditional model that ignores the supercooling effect or uses the initial droplet profile. The model reduces the deviation of freezing time from about 30% to about 10% for both hydrophilic and hydrophobic surfaces. With use of the average value of the freezing times yielded by the numerical and theoretical models, a correlation is developed for predicting the freezing time. It can correlate more than 90% of the simulation data and all of the experimental points within ±25%. As the cold plate temperature, droplet volume and contact angle increase, the freezing time increases, with the plate temperature and contact angle possessing a more significant influence than the droplet volume on the freezing process.

中文翻译:

特别关注过冷和体积膨胀效应的过冷固着水滴冷冻模拟与实验

摘要 对过冷水滴在冷板上的冻结过程进行了实验和数值研究。建立了一个同时考虑物理性质的过冷效应和体积膨胀对液滴冻结曲线的影响的数值模型,以使用凝固/熔化模型模拟液滴冻结行为。在亲水和疏水表面上对 5、10、20、30 和 40 μL 过冷水滴进行了实验。使用图像识别技术观察液滴冻结行为,包括冻结前沿运动和冻结时间。与忽略过冷效应或使用初始液滴轮廓的传统模型相比,数值模型计算出的冻结锋的演化与实验观察更符合。该模型将亲水和疏水表面的冷冻时间偏差从约 30% 降低到约 10%。使用由数值模型和理论模型产生的冻结时间的平均值,开发了用于预测冻结时间的相关性。它可以将超过 90% 的仿真数据和±25% 以内的所有实验点相关联。随着冷板温度、液滴体积和接触角的增加,冷冻时间增加,其中板温度和接触角对冷冻过程的影响比液滴体积更显着。建立相关性来预测冻结时间。它可以将超过 90% 的仿真数据和±25% 以内的所有实验点相关联。随着冷板温度、液滴体积和接触角的增加,冷冻时间增加,其中板温度和接触角对冷冻过程的影响比液滴体积更显着。建立相关性来预测冻结时间。它可以将超过 90% 的仿真数据和±25% 以内的所有实验点相关联。随着冷板温度、液滴体积和接触角的增加,冷冻时间增加,其中板温度和接触角对冷冻过程的影响比液滴体积更显着。
更新日期:2018-12-01
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