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Direct numerical simulations for liquid metal applications 241

profiles at low Reynolds numbers accessible by DNS (Fig. 6.1.1.2) are similar to par-
abolic laminar flow profiles due to the high diffusive heat fluxes, which are typically
much larger than turbulent heat fluxes, see Fig. 6.1.1.4.
Further differences are in the temperature fluctuations at the liquid-solid wall: due
to the comparable liquid and solid properties, turbulent temperature fluctuations pen-
etrate into the solid walls much more efficiently than in the liquid water-solid systems.
Another property of low Prandtl number liquid heat transfer is the nonnegligible
role of the large-scale structures, which are practically irrelevant in the velocity field
statistics. The mean temperature profiles remain unaffected by the large-scale turbu-
lent structures, while their contribution to the temperature RMS fluctuations
(Fig. 6.1.1.3) is not negligible and can account for up to 20% of the total fluctuations.
The presence of the large-scale structures becomes visible in the measurable temper-
ature statistics only at Prandtl numbers around 0.01 or lower. The observed large-scale
thermal structures can be understood as echoes of the weak large-scale structures hid-
den in the velocity field. They should be seen also in the statistics of the LES studies.
The focus of the state-of-the-art studies in the field of low Prandtl number fluids is
nowadays on buoyant flows, and on slightly more complex geometries. A few exam-
ples are mentioned in this text: wavy channel flow, flow over a BFS, and buoyant flow
in the subchannel. The last two cases are under development and represent the con-
tribution of research groups of the authors to the EU H2020 project SESAME. How-
ever, two main problems remain: extraction of information from DNS and statistical
uncertainties. It is not always clear what is the useful information in the huge amount
of DNS data and it is not always easy to extract it. Nevertheless, the role of the DNS
benchmarks, which are performed in such geometries, remains crucial for develop-
ment and improvement of turbulence models in LES and RANS approaches.

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