A Bayesian inference framework with Gaussian likelihood and inverse-Gamma priors analytically updates Galerkin-POD ODE coefficients to improve stability and accuracy for unsteady compressible flows, validated on dimpled-surface oscillation and centrifugal compressor cases.
Rempfer, Investigations of boundary layer transition via galerkin projections on empirical eigenfunctions, Physics of Fluids8, 175 (1996)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.flu-dyn 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Bayesian-Enhanced Galerkin-Based Reduced Order Modelling for Unsteady Compressible Flows
A Bayesian inference framework with Gaussian likelihood and inverse-Gamma priors analytically updates Galerkin-POD ODE coefficients to improve stability and accuracy for unsteady compressible flows, validated on dimpled-surface oscillation and centrifugal compressor cases.