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Integrated CFD-aided theoretical demonstration of cavitation modulation in self-sustained oscillating jets.

Authors :
Liu, Wenchuan
Kang, Yong
Wang, Xiaochuan
Liu, Qi
Fang, Zhenlong
Source :
Applied Mathematical Modelling. Mar2020, Vol. 79, p521-543. 23p.
Publication Year :
2020

Abstract

• A modified model regarding the viscosity and cavitation criterion was proposed and validated by experimental results. • Various numerical models were evaluated and the turbulence stress should be considered. • Fluid network and wave theory were used to elucidate different modulation mechanism in self-sustained resonating jet. • Cavitation evolution dominates the oscillation frequency of LF nozzle via modifying disturbed volume. • Geometry resonance couples with cavitation collapse and growth to achieve frequency modulation in HF nozzle. Self-sustained oscillating jets are widely utilized in various industries, and their oscillation frequencies are closely related to their performance efficiencies. The oscillation frequency is affected by cavitation in practical situations, and cavitation effects vary with geometry. In the present study, the computation fluid dynamics (CFD)-aided method is used to investigate the different modulation mechanisms induced by cavitation in high-frequency (HF) and low-frequency (LF) nozzles. The results indicate that the modified numerical model can reproduce the cavitation evolution in different nozzles and provide information to aid theoretical and experimental analyses. Based on the wave theory, it is found that the cavitation structures determine the LF nozzle oscillation frequency by dominating the disturbed volume bounded by the shear layer and chamber walls. In the case of HF nozzle, the growth and collapse of cavitation are regarded as the major excitation sources affecting oscillation frequency. In addition, the frequency is predicted using the CFD-aided method at various cavitation numbers, which is beneficial to the utilization of self-sustained oscillating jets. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0307904X
Volume :
79
Database :
Academic Search Index
Journal :
Applied Mathematical Modelling
Publication Type :
Academic Journal
Accession number :
141117154
Full Text :
https://doi.org/10.1016/j.apm.2019.10.050