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

The objective of the present study is to provide a numerical database ofthermal boundary layers and to contribute to the understanding of the dynamicsof passive scalars at different Prandtl numbers. In this regard, a directnumerical simulation (DNS) of an incompressible zero-pressure-gradientturbulent boundary layer is performed with the Reynolds number based onmomentum thickness $Re_{\theta}$ up to $1080$. Four passive scalars,characterized by the Prandtl numbers $Pr = 1,2,4,6$ are simulated with constantDirichlet boundary conditions, using the pseudo-spectral code SIMSON (Chevalieret al. 2007). To the best of our knowledge, the present direct numericalsimulation provides the thermal boundary layer with the highest Prandtl numberavailable in the literature. It corresponds to that of water at$\sim$24$^{o}C$, when the fluid temperature is considered as a passive scalar.Turbulence statistics for the flow and thermal fields are computed and comparedwith available numerical simulations at similar Reynolds numbers. The mean flowand temperature profiles, root-mean squared (RMS) velocity and temperaturefluctuations, turbulent heat flux, turbulent Prandtl number and higher-orderstatistics agree well with the numerical data reported in the literature.Furthermore, the pre-multiplied two-dimensional spectra of the velocity and ofthe passive scalars are computed, providing a quantitative description of theenergy distribution at the different lengthscales for various wall-normallocations. The energy distribution of the heat flux fields at the wall isconcentrated on longer temporal structures and exhibits different footprint atthe wall, with increasing Prandtl number.

Direct numerical simulation of a zero-pressure-gradient thermal turbulent boundary layer up to $\textrm{Pr = 6}$