Data-Driven Calibration of Rough Heat Transfer Prediction Using Bayesian Inversion and Genetic Algorithm

Data-Driven Calibration of Rough Heat Transfer Prediction Using Bayesian Inversion and Genetic Algorithm

The prediction of heat transfers in Reynolds-Averaged Navier–Stokes (RANS) simulations requires corrections for rough surfaces. The turbulence models are adapted to cope with surface roughness impacting the near-wall behaviour compared to a smooth surface. These adjustments in the models correctly p...

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Bibliographic Details
Main Authors: Kevin Ignatowicz, Elie Solaï, François Morency, Héloïse Beaugendre
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Energies
Subjects:
Bayesian inversion
genetic algorithm
data-driven analysis
calibration
rough heat transfers
computational fluid dynamics
Online Access:https://www.mdpi.com/1996-1073/15/10/3793

Internet

https://www.mdpi.com/1996-1073/15/10/3793

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