Downscaling data assimilation algorithm with applications to statistical solutions of the Navier–Stokes equations

dc.contributor.authorBiswas, Animikh
dc.contributor.authorFoias, Ciprian
dc.contributor.authorMondaini, Cecilia F.
dc.contributor.authorTiti, Edriss S.
dc.date.accessioned2024-11-14T15:18:23Z
dc.date.available2024-11-14T15:18:23Z
dc.date.issued2018-06-06
dc.description.abstractBased on a previously introduced downscaling data assimilation algorithm, which employs a nudging term to synchronize the coarse mesh spatial scales, we construct a determining map for recovering the full trajectories from their corresponding coarse mesh spatial trajectories, and investigate its properties. This map is then used to develop a downscaling data assimilation scheme for statistical solutions of the two-dimensional Navier–Stokes equations, where the coarse mesh spatial statistics of the system is obtained from discrete spatial measurements. As a corollary, we deduce that statistical solutions for the Navier–Stokes equations are determined by their coarse mesh spatial distributions. Notably, we present our results in the context of the Navier–Stokes equations; however, the tools are general enough to be implemented for other dissipative evolution equations.
dc.description.sponsorshipThe authors would like to thank Prof. Ricardo Rosa for stimulating and helpful discussions. The work of A.B. was supported in part by the NSF grant DMS 1517027, that of C.F. was supported in part by the NSF grant DMS 1516866 and the ONR grant N00014-15-1-2333. The work of C.F.M. and E.S.T. was partially supported by the ONR grant N00014-15-1-2333.
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S0294144918300684
dc.format.extent54 pages
dc.genrejournal articles
dc.genrepreprints
dc.identifierdoi:10.13016/m2mdzb-0b1i
dc.identifier.citationBiswas, Animikh, Ciprian Foias, Cecilia F. Mondaini, and Edriss S. Titi. “Downscaling Data Assimilation Algorithm with Applications to Statistical Solutions of the Navier–Stokes Equations.” Annales de l’Institut Henri Poincaré C, Analyse Non Linéaire 36, no. 2 (March 1, 2019): 295–326. https://doi.org/10.1016/j.anihpc.2018.05.004.
dc.identifier.urihttps://doi.org/10.1016/j.anihpc.2018.05.004
dc.identifier.urihttp://hdl.handle.net/11603/36913
dc.language.isoen
dc.publisherElsevier
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Mathematics and Statistics Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectData assimilation
dc.subjectDetermining form
dc.subjectDownscaling
dc.subjectNavier–Stokes equations
dc.subjectNudging
dc.subjectVishik–Fursikov statistical solutions
dc.titleDownscaling data assimilation algorithm with applications to statistical solutions of the Navier–Stokes equations
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0001-8594-0568

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1s2.0S0294144918300684am.pdf
Size:
707.83 KB
Format:
Adobe Portable Document Format