Abstract Results of detailed analysis of temperature fields in droplets of four widely used liquids (water, kerosene, Diesel and gasoline (petroleum oil) fuels) are presented. Single droplets suspended on a wire were heated in a flow of hot air. The initial droplet radii were in the range 1 to 2 mm, air temperature was in the range 20 ∘C to 500 ∘C, air flow velocity was 3-3.5 m/s. The droplet temperature was measured based on Laser Induced Phosphorescence (LIP). BAM:Eu (BaMgAl10O17:Eu 2 + ) microparticles were introduced into the droplets for the emission of a temperature-sensitive phosphorescent signal. Optical sectioning inside the droplet was performed using a thin laser sheet, while two cameras detected the phosphorescence signal in two spectral bands. A ratiometric approach using the pixel-to-pixel ratio of the images recorded by the two cameras allowed us to determine the local temperature within the heated and evaporating droplet. The range of applicability and the advantages/shortcomings of the method are established alongside the sources of errors. The experimentally observed droplet surface temperatures are compared with the predictions of the customised version of ANSYS Fluent with the Effective Thermal Conductivity (ETC) model implemented into it via User Defined Functions (UDF). It is shown that ANSYS Fluent can correctly predict the trend of the time evolution of these temperatures.

中文翻译：

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激光诱导磷光法在加热蒸发液滴温度分布分析中的应用

摘要 介绍了四种广泛使用的液体（水、煤油、柴油和汽油（石油）燃料）液滴中温度场的详细分析结果。悬浮在金属丝上的单个液滴在热空气流中被加热。初始液滴半径范围为 1 至 2 mm，空气温度范围为 20 ∘C 至 500 ∘C，空气流速为 3-3.5 m/s。基于激光诱导磷光 (LIP) 测量液滴温度。BAM:Eu (BaMgAl10O17:Eu 2 + ) 微粒被引入液滴中以发射温度敏感的磷光信号。使用薄激光片对液滴内部进行光学切片，同时两个相机检测到两个光谱带中的磷光信号。使用两个相机记录的图像的像素与像素比的比率方法使我们能够确定加热和蒸发的液滴内的局部温度。该方法的适用范围和优点/缺点与错误来源一起确定。将实验观察到的液滴表面温度与通过用户定义函数 (UDF) 在其中实施有效热导率 (ETC) 模型的定制版 ANSYS Fluent 的预测进行比较。结果表明，ANSYS Fluent 能够正确预测这些温度随时间演变的趋势。该方法的适用范围和优点/缺点与错误来源一起确定。将实验观察到的液滴表面温度与通过用户定义函数 (UDF) 在其中实施有效热导率 (ETC) 模型的定制版 ANSYS Fluent 的预测进行比较。结果表明，ANSYS Fluent 能够正确预测这些温度随时间演变的趋势。该方法的适用范围和优点/缺点与错误来源一起确定。将实验观察到的液滴表面温度与通过用户定义函数 (UDF) 在其中实施有效热导率 (ETC) 模型的定制版 ANSYS Fluent 的预测进行比较。结果表明，ANSYS Fluent 能够正确预测这些温度随时间演变的趋势。