Pipe flow simulation data illustrating the influence of filter kernels on the scale-energetics of near-wall turbulence

Originally developed for large-eddy simulation (LES) modelling and error estimation, the concept of inter-scale energy fluxes, π λ, is now widely used as a diagnostic tool to study how energy is transferred across different length scales, λ, in high-resolution turbulence data---independent of LES modelling. In Feldmann et al. (2025), we examine how the choice of filter kernel affects the computed energy fluxes and their interpretation when π is used in post-processing to explore scale interactions in near-wall turbulence. To this end, spatial filtering is applied to a turbulent pipe flow simulation using three commonly used kernels: sharp spectral, Gaussian, and box. The dataset enables a detailed comparison of how these different filters influence both the local structure and statistical characteristics of π at constant filter width. These data support the findings presented in Feldmann et al. (2025) and are provided to facilitate further studies on filtering effects and energy transfer in wall-bounded turbulent flows. This dataset includes velocity fields and energy flux fields based on three different filter kernels, as well as one- and two-point statistics for all field data sets.