Liouville models of particle-laden flow
Physics of Fluids(2024)
摘要
Langevin (stochastic differential) equations are routinely used to describe
particle-laden flows. They predict Gaussian probability density functions
(PDFs) of a particle's trajectory and velocity, even though experimentally
observed dynamics might be highly non-Gaussian. Our Liouville approach
overcomes this dichotomy by replacing the Wiener process in the Langevin models
with a (small) set of random variables, whose distributions are tuned to match
the observed statistics.
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