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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Data-driven dimensionality reduction methods such as proper orthogonaldecomposition (POD) and dynamic mode decomposition (DMD) have proven to beuseful for exploring complex phenomena within fluid dynamics and beyond. Awell-known challenge for these techniques is posed by the continuoussymmetries, e.g. translations and rotations, of the system under considerationas drifts in the data dominate the modal expansions without providing aninsight into the dynamics of the problem. In the present study, we address thisissue for fluid flows in rectangular channels by formulating a continuoussymmetry reduction method that eliminates the translations in the streamwiseand spanwise directions simultaneously. We demonstrate our method by computingthe symmetry-reduced dynamic mode decomposition (SRDMD) of sliding windows ofdata obtained from the transitional plane-Couette and turbulentplane-Poiseuille flow simulations. In the former setting, SRDMD captures thedynamics in the vicinity of the invariant solutions with translationsymmetries, i.e. travelling waves and relative periodic orbits, whereas in thelatter, our calculations reveal episodes of turbulent time evolution that canbe approximated by a low-dimensional linear expansion.

Symmetry-reduced Dynamic Mode Decomposition of Near-wall Turbulence