Wall-Resolved Large-Eddy Simulation of Flow over a Parametric Set of Gaussian Bumps

Abstract

Wall-resolved large-eddy simulations were carried out for the flow over a parametric set of Gaussian bumps, which are representative of surfaces generating smooth-body separation. The geometry and flow conditions were motivated by an experimental investigation, which was conducted in order to provide data for validating numerical approaches. Because the high-Reynolds-number and three-dimensional shape of the experimental model is challenging, even for approximate numerical techniques, a prior investigation was initiated in order to provide benchmark results that are accessible via wall-resolved large-eddy simulation. It was found that by increasing the bump height, the Reynolds number could be reduced, and flow separation would occur. The modified bump now serves as a surrogate for the original Gaussian bump, producing smooth-body separation. In the present study, solutions are obtained to the unsteady three-dimensional compressible Navier–Stokes equations utilizing a high-fidelity computational scheme and an implicit time-marching approach. A series of simulations is carried out for bumps of varying heights, for both the three-dimensional configuration and a spanwise-periodic subset, corresponding to flow at the midspan. A number of metrics are provided to attest to the accuracy of simulations. Comparisons are made between the spanwise-periodic subset and the three-dimensional configuration, and features of the flowfields are described. The generation of an arch vortex structure evolving about the speed bump geometry is elucidated.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2024
Source ID
10.2514/1.j063320

Entities

People

  • Daniel J. Garmann
  • Donald P. Rizzetta

Organizations

  • Air Force Office of Scientific Research
  • Air Force Research Laboratory

Tags

Fields of Study

  • Physics

Readers

  • Aerodynamics/Aeronautics.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Materials Science.