3 papers
cs.CE2026
A comparison of Markov Chain Monte Carlo algorithms for Bayesian inference of constitutive models
Aricia Rinkens, Rodrigo L. S. Silva, Erik Quaeghebeur +2
Employing Bayesian inference to calibrate constitutive model parameters has grown substantially in recent years. Among the available techniques, Markov Chain Monte Carlo (MCMC) sam…
physics.flu-dyn2026
Bayesian Model Selection for Complex Flows of Yield Stress Fluids
Aricia Rinkens, Clemens V. Verhoosel, Alexandra Alicke +2
Modeling yield stress fluids in complex flow scenarios presents significant challenges, particularly because conventional rheological characterization methods often yield material…
physics.flu-dyn2023
Uncertainty quantification for the squeeze flow of generalized Newtonian fluids
Aricia Rinkens, Clemens V. Verhoosel, Nick O. Jaensson
The calibration of rheological parameters in the modeling of complex flows of non-Newtonian fluids can be a daunting task. In this paper we demonstrate how the framework of Uncerta…