English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The aim of this paper is to provide a stochastic version under locationuncertainty of the compressible Navier-Stokes equations. The modelling underlocation uncertainty setting is used here to derive a physically consistentstochastic dynamical system for compressible flows. It relies on an extendedstochastic version of the Reynolds transport theorem involving stochasticsource terms. In a similar way as in the deterministic case, this conservationtheorem is applied to density, momentum and total energy in order to obtain atransport equation of the primitive variables, i.e. density, velocity andtemperature. For the modelling of ocean dynamics, the transport of massfraction of species, such as salinity, is also considered. We show thatperforming low Mach and Boussinesq approximations to this more general set ofequations allows us to recover previous versions of incompressible stochasticNavier-Stokes equations and the stochastic Boussinesq equations, respectively.Finally, we provide some research directions on the use of this general set ofequations in the perspective of relaxing the Boussinesq and hydrostaticapproximation for ocean modelling.

Stochastic compressible Navier-Stokes equations under location uncertainty and its approximations for ocean modelling