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Uncertainty quantification of RANSE and BEM models for hydrodynamic performance of supercavitating hydrofoils
Citation Link: https://doi.org/10.15480/882.9296
Publikationstyp
Conference Paper
Date Issued
2024-04-04
Sprache
English
Author(s)
Virginia Tech, Blacksburg, VA, USA
Virginia Tech, Blacksburg, VA, USA
Yamaha Motor Corporation, Atlanta, GA, USA
TORE-DOI
Start Page
1
End Page
8
Citation
8th International Symposium on Marine Propulsors (smp 2024)
Contribution to Conference
Publisher
Norwegian University of Science and Technology, Department of Marine Technology
ISSN
2414-6129
ISBN
978-82-691120-5-4
Peer Reviewed
true
Innovating, testing, and design of supercavitating propellers and hydrofoils used in high-speed marine crafts can be time consuming and expensive. Various numerical methods and Computational Fluid Dynamics (CFD) models can help in the design and optimization processes and hence improve the efficiency of the production pipeline. This study explores the capabilities of Unsteady RANSE based CFD simulations and a potential based, low order, 2D Boundary Element Method (BEM) in predicting the performance and cavitation patterns for a 2D supercavitating hydrofoil. The goal of this study is to quantify the uncertainty in these performance prediction approaches by validating their results against available experimental data. The study revealed that unsteady RANSE, using the 𝑘 − 𝜔 turbulence model and the full Rayleigh-Plesset cavitation model predicts the most accurate hydrodynamic performance parameters. However, the most accurate cavitation patterns were predicted using the 𝑘 − 𝜖 turbulence model and the Schnerr-Sauer cavitation model. The low order BEM also showed results that agreed well with the experimental data, especially considering the approximation of the model. A further investigation on the influence of control parameter in CFD simulations showed that seed density and seed diameter can have significant influence on the cavitation pattern prediction.
Subjects
Supercavitation
Propellers
CFD
BEM
Uncertainty quantification
DDC Class
620: Engineering
Publication version
publishedVersion
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Name
Srivastava-UncertaintyQuantificationOfRanseAndBemModelsForHydrodynamicPerfo-1163-1-final.pdf
Type
Main Article
Size
1.89 MB
Format
Adobe PDF