Pressure swirl atomizers are widely applied in daily life and production activities. The spray angle is one of the most important parameters for the pressure swirl atomizers and mainly affects the spatial distribution of sprays and droplets. The quick prediction of the spray angle is important for the design and optimization of a pressure swirl atomizer. In the present study, the effects of length of swirl chamber, liquid viscosity and pressure differential on the hollow cone spray angle are studied by experiments. An available semi-empirical correlation for hollow cone spray angle prediction is derived by proper assumptions and simplification. This available correlation is validated by comparison with the experimental results. Besides, other correlations based on inviscid flow and viscous flow are also introduced to predict the spray angle for comparison. Based on the experimental results, the measured hollow cone spray angle decreases with the increasing of length of swirl chamber and liquid viscosity nonlinearly. The measured hollow cone spray angle shows no obvious growth with the increasing of the pressure differential when the pressure differential reaches a critical value. Further, the hollow cone spray angles predicted by the present available correlation agree well with the experimental results. The prediction uncertainties can be within ±15% for all cases. While, the prediction uncertainties are no less than ±40% by other correlations. Compared with previous correlations, the present available correlation can achieve better prediction accuracy. This available correlation is capable for the quick prediction of the viscous hollow cone spray angle.

中文翻译：

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关键参数对粘性空心锥喷雾角的影响以及喷雾角预测的可用相关性

压力旋流雾化器广泛应用于日常生活和生产活动中。喷雾角度是压力旋流雾化器最重要的参数之一，主要影响喷雾和液滴的空间分布。喷雾角度的快速预测对于压力旋流雾化器的设计和优化具有重要意义。本研究通过实验研究了涡流室长度、液体粘度和压差对空心锥喷射角的影响。通过适当的假设和简化推导出空心锥喷射角预测的可用半经验相关性。通过与实验结果进行比较来验证这种可用的相关性。除了，还引入了基于非粘性流和粘性流的其他相关性来预测喷雾角度以进行比较。实验结果表明，实测空心锥喷射角随涡流室长度和液体粘度的增加呈非线性减小。当压差达到临界值时，实测的空心锥喷射角随压差的增加没有明显的增长。此外，目前可用的相关性预测的空心锥形喷雾角度与实验结果很好地吻合。对于所有情况，预测不确定性可以在 ±15% 以内。而其他相关性的预测不确定性不小于±40%。与以前的相关性相比，目前可用的相关性可以实现更好的预测精度。