Investigation of sheet to cloud cavitation dynamics using modal decomposition

The objective of this study is to apply modal decomposition methods to numerical simulations of sheet to cloud cavitation over a wedge. A homogeneous mixture model is employed, and the numerical method is first validated against experimental measurements, showing good agreement across a range of cavitation numbers. The simulations capture the two primary mechanisms known to destabilize the sheet cavity: the re-entrant jet mechanism and the condensation front mechanism. The results confirm that a homogeneous mixture model composed of incompressible liquid and vapor phases is adequate to capture the formation of a condensation front, suggesting that individual phase compressibility is not an essential condition for its formation. Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) are then used to analyze dominant flow structures within a single cavity shedding cycle. The modal analysis shows distinct spatial modes delineating the two instability routes. At relatively low cavitation numbers, the leading POD mode and DMD mode capture a wall-detached vapor structure that travels upstream as a condensation front, accompanied by pressure variations inside the partial cavity. At higher cavitation numbers, the dominant modes show a thin, wall-attached vapor structure that advances upstream as a re-entrant jet accompanied by pressure variations outside the partial cavity. The identification of these dominant spatial modes for each of the mechanisms presents an opportunity to design appropriate control strategies to modulate sheet to cloud cavitation transition at different cavitation numbers.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2025-12-01
DOI
https://doi.org/10.1063/5.0304009
Primary Topic
Cavitation Phenomena in Pumps
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigation of sheet to cloud cavitation dynamics using modal decomposition

Aswin Gnanaskandan, Mahdi Lavari
Physics of Fluids
Cavitation Phenomena in Pumps
article

Investigation of sheet to cloud cavitation dynamics using modal decomposition

Aswin Gnanaskandan, Mahdi Lavari
article en

Abstract

The objective of this study is to apply modal decomposition methods to numerical simulations of sheet to cloud cavitation over a wedge. A homogeneous mixture model is employed, and the numerical method is first validated against experimental measurements, showing good agreement across a range of cavitation numbers. The simulations capture the two primary mechanisms known to destabilize the sheet cavity: the re-entrant jet mechanism and the condensation front mechanism. The results confirm that a homogeneous mixture model composed of incompressible liquid and vapor phases is adequate to capture the formation of a condensation front, suggesting that individual phase compressibility is not an essential condition for its formation. Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) are then used to analyze dominant flow structures within a single cavity shedding cycle. The modal analysis shows distinct spatial modes delineating the two instability routes. At relatively low cavitation numbers, the leading POD mode and DMD mode capture a wall-detached vapor structure that travels upstream as a condensation front, accompanied by pressure variations inside the partial cavity. At higher cavitation numbers, the dominant modes show a thin, wall-attached vapor structure that advances upstream as a re-entrant jet accompanied by pressure variations outside the partial cavity. The identification of these dominant spatial modes for each of the mechanisms presents an opportunity to design appropriate control strategies to modulate sheet to cloud cavitation transition at different cavitation numbers.

Physics of FluidsVol. 37(12)
Worcester Polytechnic Institute (US)
Openalex Percentile: Top 57%
Cavitation Phenomena in Pumps
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.