.png){kind=icon}
.png){kind=icon}
Return
Multi-objective and multi-point adjoint optimization of diverterless supersonic inlet
.png){kind=icon}
OA
AI
C
D
J
邓
C
L
C
DOI：10.1016/j.dt.2026.07.017.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Modern combat aircraft require a wide operating speed range, posing a fundamental trade-off in diverterless supersonic inlet design between supersonic and subsonic aerodynamic performance. This study addresses this conflict through a multi-objective, multi-design-point optimization using a full-process adjoint method based on surface sensitivity. Two optimization strategies are formulated and compared. The first directly linearly weights total pressure recovery and circumferential distortion at both supersonic and subsonic design points. The second treats supersonic performance as the objective while imposing subsonic performance as a penalty constraint. Results reveal that under direct linear weighting, subsonic improvement dominates, yielding limited supersonic gains. Obtaining Pareto solutions under this strategy requires assigning an extremely high weight to total pressure recovery. Within the same weight space, the penalty constraint strategy suppresses the dominance of subsonic enhancement and unlocks further supersonic improvement. This strategy produces more Pareto solutions by intensifying the counter rotating vortex near the duct centerline inflection point, which reduces internal distortion and transforms previously non Pareto points into Pareto optimal ones. The aerodynamic throat area is identified as the central mechanism governing the supersonic subsonic compromise. Optimized configurations exhibit a subcritical compression wave system at the bump, with increased throat area and mass flow when subsonic performance is emphasized. These findings provide a physically grounded framework for reconciling wide speed range performance conflicts in fixed geometry supersonic inlets.
Keywords:
Devierterless supersonic inlet
Multi-objective
Multi-point
Aerodynamic optimization
Adjoint equations
Surface sensitivity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.9K
Citations:
6.4K
Organization
Cited Papers