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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | University of Sheffield |
| Country | United Kingdom |
| Start Date | Jan 11, 2021 |
| End Date | Sep 10, 2024 |
| Duration | 1,338 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | UKRI Gateway to Research |
| Grant ID | EP/T01167X/1 |
Compressible boundary-layer flows over concave surfaces, characterized by Gortler vortices, are ubiquitous in a large number of fluid engineering applications, such as turbine blades, high-speed aircraft wings, and nozzles in supersonic wind tunnels.
The overall objectives of this proposed work are to numerically investigate spatially developing compressible boundary layers over concave surfaces, from the laminar regime up to the fully turbulent regime, and to advance both the fundamental understanding and prediction of Gortler-vortex-induced transition and spatially developing wall-bounded turbulence subject to concave surface curvature at supersonic Mach numbers.
The research will be conducted jointly by UK and US investigators who perfectly complement each other.
The detailed study of boundary-layer physics will also be combined with large-eddy simulations and Reynolds-averaged Navier-Stokes (RANS) to assess the performance of subgrid-scale and RANS models for transitional flows dominated by Gortler vortices.
Because RANS models lack the physical basis necessary to include the effects of the upstream history on boundary-layer disturbances, the DNS data will be compared with RANS-based predictions to assess the quality of the computation of the initial turbulent region.
The data can also be used to evaluate the ability of LES to reproduce the transition zone for different LES filter characteristics.
In conjunction with the research effort, a variety of educational activities will be undertaken to showcase and instil the excitement of cyberphysics discovery in students at all levels, as well as to prepare a highly-trained workforce in high-speed flows and advanced cyberinfrastructure.
University of Sheffield
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