Geometry of turbulent dissipation and the Navier–Stokes regularity problem
Abstract The question of whether a singularity can form in an initially regular flow, described by the 3D incompressible Navier–Stokes (NS) equations, is a fundamental problem in mathematical physics. The NS regularity problem is super-critical, i.e., there is a ‘scaling gap’ between what can be est...
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Nature Portfolio
2021
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oai:doaj.org-article:0ba91c502e23493995c73a0c85e2448f2021-12-02T18:27:50ZGeometry of turbulent dissipation and the Navier–Stokes regularity problem10.1038/s41598-021-87774-y2045-2322https://doaj.org/article/0ba91c502e23493995c73a0c85e2448f2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87774-yhttps://doaj.org/toc/2045-2322Abstract The question of whether a singularity can form in an initially regular flow, described by the 3D incompressible Navier–Stokes (NS) equations, is a fundamental problem in mathematical physics. The NS regularity problem is super-critical, i.e., there is a ‘scaling gap’ between what can be established by mathematical analysis and what is needed to rule out a singularity. A recently introduced mathematical framework—based on a suitably defined ‘scale of sparseness’ of the regions of intense vorticity—brought the first scaling reduction of the NS super-criticality since the 1960s. Here, we put this framework to the first numerical test using a spatially highly resolved computational simulation performed near a ‘burst’ of the vorticity magnitude. The results confirm that the scale is well suited to detect the onset of dissipation and provide numerical evidence that ongoing mathematical efforts may succeed in closing the scaling gap.Janet RafnerZoran GrujićChristian BachJakob Andreas BærentzenBo GervangRuo JiaScott LeinweberMarek MisztalJacob ShersonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021) |
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Medicine R Science Q Janet Rafner Zoran Grujić Christian Bach Jakob Andreas Bærentzen Bo Gervang Ruo Jia Scott Leinweber Marek Misztal Jacob Sherson Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
description |
Abstract The question of whether a singularity can form in an initially regular flow, described by the 3D incompressible Navier–Stokes (NS) equations, is a fundamental problem in mathematical physics. The NS regularity problem is super-critical, i.e., there is a ‘scaling gap’ between what can be established by mathematical analysis and what is needed to rule out a singularity. A recently introduced mathematical framework—based on a suitably defined ‘scale of sparseness’ of the regions of intense vorticity—brought the first scaling reduction of the NS super-criticality since the 1960s. Here, we put this framework to the first numerical test using a spatially highly resolved computational simulation performed near a ‘burst’ of the vorticity magnitude. The results confirm that the scale is well suited to detect the onset of dissipation and provide numerical evidence that ongoing mathematical efforts may succeed in closing the scaling gap. |
format |
article |
author |
Janet Rafner Zoran Grujić Christian Bach Jakob Andreas Bærentzen Bo Gervang Ruo Jia Scott Leinweber Marek Misztal Jacob Sherson |
author_facet |
Janet Rafner Zoran Grujić Christian Bach Jakob Andreas Bærentzen Bo Gervang Ruo Jia Scott Leinweber Marek Misztal Jacob Sherson |
author_sort |
Janet Rafner |
title |
Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
title_short |
Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
title_full |
Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
title_fullStr |
Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
title_full_unstemmed |
Geometry of turbulent dissipation and the Navier–Stokes regularity problem |
title_sort |
geometry of turbulent dissipation and the navier–stokes regularity problem |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/0ba91c502e23493995c73a0c85e2448f |
work_keys_str_mv |
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1718377961690759168 |