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Труды Института механики им. Р.Р. Мавлютова
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Proceedings of the Mavlyutov Institute of Mechanics


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Troian R., Dragna D., Bailly C., Galland M.-A. Broadband liner impedance eduction for multimodal acoustic propagation in the presence of a mean flow // Proceedings of the Mavlyutov Institute of Mechanics. 2016. 11(2). Pp. 150–155.
2016. Vol. 11. Issue 2, Pp. 150–155
URL: http://proc.uimech.org/uim2016.2.022,en
DOI: 10.21662/uim2016.2.022
Broadband liner impedance eduction for multimodal acoustic propagation in the presence of a mean flow
Troian R., Dragna D.∗∗, Bailly C.∗∗, Galland M.-A.∗∗
Normandie universite, LOFIMS/INSA de ROUEN, France
∗∗Laboratoire de Mécanique des Fluides et d’Acoustique, Centre Acoustique, LMFA, ECL, France

Abstract

Modeling of acoustic propagation in a duct with absorbing treatment is considered. The surface impedance of the treatment is sought in the form of a rational fraction. The numerical model is based on a resolution of the linearized Euler equations by finite difference time domain for the calculation of the acoustic propagation under a grazing flow. Sensitivity analysis of the considered numerical model is performed. The uncertainty of the physical parameters is taken into account to determine the most influential input parameters. The robustness of the solution vis-a-vis changes of the flow characteristics and the propagation medium is studied.

Keywords

sensitivity,
grazing flow,
impedance,
Sobol’s method

This work was performed within the framework of the Labex CeLyA of Université de Lyon, the program ”Investissements d’Avenir” (ANR-10-LABX-0060/ ANR-11-IDEX-0007) operated by the French National Research Agency (ANR) and was carried out in collaboration with Aircelle(technical monitor Marc Versaevel). The authors would like to acknowledge the financial support from the European Union Seventh Framework Programme (FP7) through the ENOVAL project under grant agreement number 604999. In addition, the authors would like to thank Dr. Michael Jones (NASA) for providing the benchmark data used for the validation.