作者简介:程西怡(2001—),男,硕士生;
郭根苗(通信作者),女,副教授,硕士生导师。
收稿:2025-03-07,
纸质出版:2025-10-10
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程西怡, 李红梅, 韩丹, 等. 喷嘴内云空化瞬态特性的湍流模型适用性研究[J]. 西安交通大学学报, 2025,59(10):160-169.
CHENG Xiyi, LI Hongmei, HAN Dan, et al. Study on the Applicability of Turbulence Model to Transient Evolution Characteristics of Cloud Cavitation in Nozzle[J]. Journal of Xi'an Jiaotong University, 2025, 59(10): 160-169.
程西怡, 李红梅, 韩丹, 等. 喷嘴内云空化瞬态特性的湍流模型适用性研究[J]. 西安交通大学学报, 2025,59(10):160-169. DOI: 10.7652/xjtuxb202510015.
CHENG Xiyi, LI Hongmei, HAN Dan, et al. Study on the Applicability of Turbulence Model to Transient Evolution Characteristics of Cloud Cavitation in Nozzle[J]. Journal of Xi'an Jiaotong University, 2025, 59(10): 160-169. DOI: 10.7652/xjtuxb202510015.
为评估不同湍流模型对喷嘴内云空化瞬态演化特性的解析能力与适用性,基于数值模拟方法,结合空化多相流模型,对剪切应力输运
k-ω
雷诺平均模型、大涡模拟、延迟分离涡模拟和超大涡模拟的解析能力对比分析。结果表明:剪切应力输运
k-ω
雷诺平均模型计算效率高,但由于采用时均化处理,难以准确捕捉云空化脱落与溃灭等瞬态行为;大涡模拟模型可精确解析小尺度涡结构与瞬态压力脉动,能够再现云空化全周期演化过程,模拟结果与可视化试验吻合良好,但计算资源消耗为剪切应力输运
k-ω
模型的4倍以上;延迟分离涡模拟因近壁面与弱旋区域仍采用雷诺时均方法,导致对脱落过程、回射流及高频压力响应的预测精度受限;超大涡模拟基于尺度自适应的动态混合雷诺时均-大涡方法,在保障脱落细节解析能力的同时,显著降低了计算资源消耗,相较大涡模拟节省约30%。此外,基于压力脉动的傅里叶变换分析显示,超大涡模拟预测的云空化脱落主频与试验偏差小于5%,验证了其在云空化建模中的准确性与高效性,具备一定的工程应用潜力。
To evaluate the resolution capability and applicability of different turbulence models in analyzing the transient evolution characteristics of cloud cavitation in nozzles
this study employs numerical simulations combined with a cavitation multiphase flow model to compare the performance of the shear stress transport (SST)
k-ω
Reynolds-averaged Navier-Stok
es (RANS) model
large eddy simulation (LES)
delayed detached-eddy simulation (DDES)
and very large eddy simulation (VLES).The results show that the SST
k-ω
model offers high computational efficiency but fails to accurately capture transient behaviors such as cloud cavitation shedding and collapse due to its time-averaged treatment. In contrast
the LES model precisely resolves small-scale vortex structures and transient pressure fluctuations
reproducing the full-cycle evolution of cloud cavitation
with simulation results closely matching visual experimental data. However
its computational cost exceeds that of the SST
k-ω
model by more than four times. DDES
due to the employment of RANS in near-wall and low-vorticity regions
exhibits limited accuracy in predicting shedding processes
re-entrant jets and high-frequency pressure responses. VLES
based on a scale-adaptive dynamic hybridRANS-LESapproach
significantly reduces computational costs
approximately 30% less than LES
while maintaining high resolution of shedding details. Furthermore
Fourier transform analysis based on pressure fluctuations reveals that VLES predicts the dominant shedding frequency of cloud cavitation with less than 5% deviation from experimental data
validating its accuracy and efficiency in cloud cavitation modeling and demonstrating its potential for engineering applications.
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