Alberto TESTA, Pierre SCHROOYEN, Guillaume GROSSIR, Johan STEELANT

DOI Number: N/A

Conference number: HiSST-2025-221

This paper presents a modular, automated framework for the early-stage aerodynamic optimization of quiet supersonic nozzles, leveraging Bayesian Optimization (BO) to minimize boundary-layer instability growth. The methodology integrates inviscid contour generation via the Method of Characteristics, viscous boundary-layer correction, and local Linear Stability Theory (LST) for transition prediction. The total amplification of first-mode and Görtler instabilities is used as the objective function, with additional constraints on nozzle compactness, manufacturability, and quiet flow length. The BO loop demonstrates rapid convergence within a limited number of evaluations, accurately identifying optimal geometries that satisfy realistic facility constraints. The framework, verified against a previously validated pipeline, reveals key insights into the impact of geometric and thermal parameters—such as throat height, expansion angle, and wall temperature distribution—on transition onset. The approach is flexible and extendable to hypersonic regimes, making it a promising tool for the next-generation quiet tunnel design.

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In Categories: 1.Events, 1.HiSST 2025, High-Speed Aerodynamics and Aerothermodynamics with application to hypersonic regimes
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