Bayesian Inference of Cavitation Model Coefficients and Uncertainty Quantification of a Venturi Flow Simulation

Bayesian Inference of Cavitation Model Coefficients and Uncertainty Quantification of a Venturi Flow Simulation

In the present work, uncertainty quantification of a venturi tube simulation with the cavitating flow is conducted based on Bayesian inference and point-collocation nonintrusive polynomial chaos (PC-NIPC). A Zwart–Gerber–Belamri (ZGB) cavitation model and RNG k-ε turbulence model are adopted to simu...

Full description

Bibliographic Details
Main Authors: Jae-Hyeon Bae, Kyoungsik Chang, Gong-Hee Lee, Byeong-Cheon Kim
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Energies
Subjects:
uncertainty quantification (UQ)
Bayesian inference
point-collocation nonintrusive polynomial chaos (PC-NIPC)
cavitation
Zwart–Gerber–Belamri (ZGB) cavitation model
in-service testing
Online Access:https://www.mdpi.com/1996-1073/15/12/4204

Internet

https://www.mdpi.com/1996-1073/15/12/4204

Similar Items