Coupled fluid–thermal analysis of the reduction mechanism for the drag and heat flux induced by jet interaction in a hypersonic reusable launch vehicle
Source abstract
Abstract
The analysis of heat transfer is crucial to hypersonic vehicles that operate under high pressure and aerodynamic heat flux due to severe aero-heating. The jet concept has been applied to reduce drag and increase thermal protection. In this paper, a flow control mechanism introduced through a jet strategy equipped on the blending area with a freestream Mach number of 6 is analyzed numerically. The thermal response of the hypersonic vehicle is numerically investigated with a three-dimensional fluid–thermal coupling approach based on a loosely coupled fluid–thermal analysis. The results indicate that, throughout the coupling process, the reduced temperature growth inside the structure contributes to lowered fluid temperature gradient, thus depressing external aerodynamic heating and gradually decreasing the rate of variation in heat flux as a consequence. The calculations focus on the influence of drag reduction on the aerodynamic characteristics of the hypersonic vehicle, and the thermal protection effects of different methods are compared. The study finds that manipulating the shock structure through jet interaction is practical and promising for alleviating high flight resistance and severe aero-heating, and the jet strategy is an advantageous means of reducing drag and thermal protection for the blending area. A maximum 2.22% increase in lift coefficient and 1.98% decrease in drag coefficient are obtained, and the lift-to-drag ratio of the vehicle is improved by 4.23% with the porous jet strategy. Moreover, this strategy remarkably reduces overall heat flux to less than 108 kW/m2 along the characteristic centerline of the jet orifices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Computational Fluid Dynamics and Aerodynamics · Gas Dynamics and Kinetic Theory · Fluid Dynamics and Turbulent Flows
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (40)
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