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Numerical Simulation of Transpiration Cooling in a Laminar Hypersonic Boundary Layer - Dataset

Documentation:
Two-dimensional simulations of transpiration cooling in a laminar, hypersonic boundary layer were performed using the thermochemical implicit nonequilibrium algorithm (TINA): a Navier–Stokes solver. Coolant concentration and heat flux results are compared to data obtained from laminar transpiration cooling experiments conducted in the Oxford High Density Tunnel employing a flat-plate geometry at Mach 7. TINA successfully predicts the mixing rate at the wall as a function of the streamwise direction for all blowing ratios. The simulations are more successful in predicting the mixing downstream of the injector as compared to the mixing on the injector: especially at low blowing ratios. A collapse of the thermal effectiveness values calculated from TINA simulation data is achieved, which agrees with laminar correlations within an absolute value of ±10%. It is shown that, when the concentration effectiveness is close to one at the injector, the temperature gradient becomes negative at locations immediately downstream of the injector, resulting in a negative heat flux. The acceleration of the coolant in the streamwise direction downstream promotes dissipation of energy, which results in a reduction in the temperature of the coolant, and thereby induces a negative temperature gradient close to the injector.

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Creator
ORCID:
0000-0002-8398-8987
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Creator
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Creator
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Institution:
Fluid Gravity Engineering Ltd
Role:
Creator


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Funding agency for:
McGilvray, M
Grant:
EP/P000878/1


Publisher:
University of Oxford
Publication date:
2022
DOI:


Language:
English
Pubs id:
1481193
Local pid:
pubs:1481193
Deposit date:
2022-11-28
ARK identifier:

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