Multi-point design optimization of a high-performance intake for scramjet-powered ascent flight

摘要

Scramjet engines are one of the most promising hypersonic airbreathing propulsion techniques for efficient and economic access to space. Besides capturing and compressing the air to desirable flow conditions, the intake plays a vital role in determining the intake drag, flow compression efficiency, started flow condition that governs the overall scramjet engine performance. For access to space, the flight trajectory practically comprises varying freestream conditions and altitude to enable ascent flight, constituting an optimization problem with off-design conditions as well as design and physical constraints to be considered. This paper presents the results and insights obtained from a first ever multi-point multi-objective optimization study of an axisymmetric scramjet intake conducted by means of surrogate-assisted evolutionary algorithms coupled with high-fidelity computational fluid dynamics. It aims to minimize the intake drag and maximize the compression efficiency at two differing conditions, i.e., Mach 7.7 at an altitude of 30 km and Mach 10 at 33.5 km. Key design factors for high-performance intakes that can achieve desirable flow compression for the combustor are identified by global sensitivity analysis and examining the trade-off characteristics. Underlying flow physics is elucidated by probing into the representative flowfields at two design conditions with adaptive mesh refinement so as to gain insights into phenomena and characteristics to realize scramjet-powered ascent flight. It has been found that the non-dominated solutions constitute clusters with respect to length and exit radius, with each cluster characterized by distinct tendencies in terms of compression efficiency loss, total drag, static pressure ratio and mean exit temperature. Shorter scramjet intakes have been found to be prone to flow separation due to impingement of a reflected shock off the centerline on the third ramp that causes an adverse pressure gradient. (c) 2020 Elsevier Masson SAS. All rights reserved.