PG-EAM - Programa de Pós-Graduação em Engenharia Aeronáutica e Mecânica
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Artigo de Conferência 2026

Toward resolvent-based estimation and control of wavepackets in supersonic turbulent jets

Autores

Zhou, Yuhao
Towne, Aaron
Jung, Junoh
Bhagwat, Rutvij
Martini, Eduardo
Jordan, Peter
Audiffred, Diego B.S.
Maia, Igor

AIAA Science and Technology Forum and Exposition AIAA Scitech Forum 2026

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Citações
9
Autores

Resumo

© 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.High-speed-jet turbulent mixing noise remains a challenging problem, and here we aim to reduce it using a wavepacket-cancellation strategy. This approach is enabled by the recently developed resolvent-based estimation and control framework, which uses near-nozzle sensors to detect noise-generating wavepackets and suppress them via actuation. This paper presents three main results toward this larger goal: (i) data-driven estimation for a Mach 1.5 supersonic jet using large-eddy simulations to identify coherent structures and inform sensor-target placement; (ii) resolvent-based estimation for the linearized jet, which achieves reasonable accuracy in reconstructing relevant flow features from limited sensor data; and (iii) preliminary resolvent-based control for the linearized jet, demonstrating a 34% reduction in the root mean square of streamwise-momentum fluctuations using only one sensor and one actuator. These findings demonstrate the potential of the resolvent-based framework for mitigating noise-generating wavepacket structures in supersonic jets and provide an important foundation for future computational and experimental investigations.

Aerospace Engineering (ENGI)
: Scopus
Última atualização: 2026-08-20
: 2-s2.0-105031096200