# Dataset to On the impact of spanwise inhomogeneous boundary conditions on secondary flows in turbulent channels

Neuhauser, Jonathan

##### Abstract:
Dieses Datenrepository enthält die wichtigsten Simulationsdaten der Masterarbeit "On the impact of spanwise inhomogeneous boundary conditions on secondary flows in turbulent channels" von Jonathan Neuhauser (2021).

Insbesondere sind die zeitlich und in Strömungsrichtung gemittelten Strömungsfelder (mittlere Geschwindigkeiten, Reynoldsspannungen, Dreifachkorrelationen, Terme der TKE-Bilanz) aller Simulationen enthalten.

Die Daten sind als komprimierte NumPy-Datei im Unterordner der jeweiligen Simulation abgelegt. Um die Auswertung zu vereinfachen, ist ein Skript (inkl. ... mehr

##### Abstract (englisch):
This data repository contains the most important simulation data of the master thesis "On the impact of spanwise inhomogeneous boundary conditions on secondary flows in turbulent channels" by Jonathan Neuhauser (2021).

In particular, the temporally and flow directionally averaged flow fields (mean velocities, Reynolds stresses, triple correlations, terms of the TKE balance) of all simulations are included.

The data are stored as a compressed NumPy file in the subfolder of the respective simulation. To simplify the evaluation, a script (incl. the pyxcompact library created in the course of the work) is included to extract the data for all figures based on the included simulations.

 Zugehörige Institution(en) am KIT Institut für Strömungsmechanik (ISTM) Publikationstyp Forschungsdaten Publikationsdatum 29.04.2021 Erstellungsdatum 01.11.2020 - 27.04.2021 Identifikator DOI (KIT): 10.5445/IR/1000131902 KITopen-ID: 1000131902 Lizenz Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 4.0 International Vorab online veröffentlicht am 27.04.2021 Schlagwörter Turbulenz, Kanalströmung, Sekundärströmung Liesmich All simulation folders contain the input file(s) for the simulation as well as the time-averaged one-point statistics of the flow. For all simulations, the following data is available: mean velocities <u>, <v>, <w> Reynolds stresses <u_i'*u_j*>, pressure correlations <u_i'*p'> Triple correlations <u_i'*u_j'*u_j'> Averaged terms of the balance of turbulent kinetic energy (TKE): Production P, Pseudo-dissipation psdiss, pressure transport ptr, turbulent transport ttrans, viscous diffusion viscdiff and mean convection mconv signed swirling strength swirl_signed Invariants eta, zeta for the Lumley triangle as well as the averaging interval, and the y and z coordinates. For some SSBC cases, time-averaged spectra have been included. Their generation is lined out in the thesis; the methods required for generating them from the raw source files are included in recreate_figures.py. The dimension factors of the data have not been altered from the XCompact3D defaults. The dimension factor for velocity may be computed based on <u> (e.g. friction velocity, bulk velocity). The viscosity, which is required to make the TKE fields dimensionless (dimension factor u_tau^4/nu) is given as nu = 1/re_cl with re_cl = (re_tau/0.116)**(1.0/0.88). A script to extract the data for the figures in the thesis is also included. This script queries the library described in the Appendix, pyxcompact. The following libraries are used (tested versions in parentheses): numpy (1.19.2) matplotlib (3.3.2) scipy(1.5.2) (for interpolation of fields) [optional] einsum2 (0.1) (increases performance of derivation calls) The script has been tested with Python 3.7.6 and Python 3.8.5. It is called as follows: python recreate_figures.py`. On executing, some console messages, indicating that files are missing, will be printed. pyxcompact normally expects the raw output files of XCompact3D in the same folder as the input file; but then proceeds to load the time-averaged file into memory. Art der Forschungsdaten Dataset
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