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April 19, 2026Physics of Fluids2 citations

Spatially local dissipation scaling in grid turbulence from direct numerical simulations

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YNYohei NishimotoKyoto UniversityKNKoji NagataTWTomoaki Watanabe

Key Points

  • The aim is to analyze the dissipation of turbulent kinetic energy in grid turbulence using local measurements.
  • Performed direct numerical simulations (DNS) of grid turbulence in a periodic box.
  • Computed global and local statistics of normalized turbulent dissipation rates.
  • Analyzed second- and third-order structure functions for intermittency effects.
  • Local dissipation rate depends strongly on local Reynolds numbers.
  • Dissipation follows a nonequilibrium scaling behavior consistent with wind tunnel measurements.
  • The local Kolmogorov constant increases with local Reynolds numbers.

Abstract

We perform a spatially defined local analysis of the normalized turbulent kinetic energy dissipation rate, Cε, using a direct numerical simulation (DNS) database of temporally developing grid turbulence in a periodic box. The mesh-based Reynolds numbers are ReM=10 000 and 20 000. Extending recent experimental local-time analyses to a fully three-dimensional flow field, we compute both global statistics over the entire domain and local statistics over spatially defined subdomains to assess nonequilibrium behavior during decay. Second- and third-order structure functions indicate negligible intermittency effects for the present cases, consistent with the relatively low turbulent Reynolds numbers Reλ. The local Cε depends strongly on the local Reλ and follows a nonequilibrium scaling, Cε/Re0∝Reλ−1, for both ReM and throughout the decay, where Re0 is the global Reynolds number. This DNS-based local scaling is consistent with wind tunnel measurements of grid-generated turbulence when analyzed using local-time frameworks. In addition, the local Kolmogorov constant C2, defined as the peak of the second-order structure function, increases with the local Reλ and exhibits trends consistent with those obtained from global statistics.

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Cite This Study

Nishimoto et al. (2026) studied this question.

synapsesocial.com/papers/69e472a8010ef96374d8eb0dhttps://doi.org/10.1063/5.0323676
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