This study assesses the predictive capability of the ZGB (Zwart-Gerber-Belamri) cavitation model with the RANS (Reynolds Averaged Navier-Stokes), the realizable k-epsilon turbulence model, and compressibility of gas/liquid models for cavitation simulation in a multi-hole fuel injector at different cavitation numbers (CN) for diesel and biodiesel fuels. The prediction results were assessed quantitatively by comparison of predicted velocity profiles with those of measured LDV (Laser Doppler Velocimetry) data. Subsequently, predictions were assessed qualitatively by visual comparison of the predicted void fraction with experimental CCD (Charged Couple Device) recorded images. Both comparisons showed that the model could predict fluid behavior in such a condition with a high level of confidence. Additionally, flow field analysis of numerical results showed the formation of vortices in the injector sac volume. The analysis showed two main types of vortex structures formed. The first kind appeared connecting two adjacent holes and is known as “hole-to-hole” connecting vortices. The second type structure appeared as double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. The use of RANS proved to save significant computational cost and time in predicting the cavitating flow with good accuracy.

这项研究评估了具有RANS（雷诺平均Navier-Stokes）的ZGB（Zwart-Gerber-Belamri）空化模型的预测能力，可实现的k-ε湍流模型以及气/液模型的可压缩性，用于在多个环境中进行空化模拟柴油和生物柴油燃料的不同气穴数（CN）的双孔喷油嘴。通过将预测的速度曲线与测得的LDV（激光多普勒测速）数据进行比较，定量地评估了预测结果。随后，通过视觉比较预测的空隙率与实验CCD（带电耦合器件）记录的图像，定性评估预测结果。两次比较均表明，该模型可以高度可信地预测这种情况下的流体行为。此外，流场分析的数值结果表明，在注射器的囊腔中形成了涡流。分析表明形成了两种主要类型的涡旋结构。第一种连接两个相邻的孔，称为“孔对孔”连接涡流。第二种类型的结构表现为从针壁出现并进入面向针孔的双“反向旋转”涡流。事实证明，使用RANS可以节省大量的计算成本和时间，从而可以很好地预测空化流。第二种类型的结构表现为从针壁出现并进入面向针孔的双“反向旋转”涡流。事实证明，使用RANS可以节省大量的计算成本和时间，从而可以很好地预测空化流。第二种类型的结构表现为从针壁出现并进入面向针孔的双“反向旋转”涡流。事实证明，使用RANS可以节省大量的计算成本和时间，从而可以很好地预测空化流。