Uncertainty Analysis in Airfoil–Turbulence Interaction Noise Using Polynomial Chaos Expansion

Kha, J; Croaker, P; Karimi, M; Skvortsov, A

Uncertainty Analysis in Airfoil–Turbulence Interaction Noise Using Polynomial Chaos Expansion

Kha, J Croaker, P Karimi, M

Skvortsov, A

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Publisher:: American Institute of Aeronautics and Astronautics
Publication Type:: Journal Article
Citation:: AIAA student journal. American Institute of Aeronautics and Astronautics, 2023, pp. 1-1
Issue Date:: 2023-11-14

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Field	Value	Language
dc.contributor.author	Kha, J
dc.contributor.author	Croaker, P
dc.contributor.author	Karimi, M https://orcid.org/0000-0002-2949-5364
dc.contributor.author	Skvortsov, A
dc.date.accessioned	2024-02-06T00:02:49Z
dc.date.available	2024-02-06T00:02:49Z
dc.date.issued	2023-11-14
dc.identifier.citation	AIAA student journal. American Institute of Aeronautics and Astronautics, 2023, pp. 1-1
dc.identifier.issn	0001-1460
dc.identifier.issn	1533-385X
dc.identifier.uri	http://hdl.handle.net/10453/175332
dc.description.abstract	<jats:p> Airfoil–turbulence interaction noise is a known source of environmental disturbance and acoustic performance loss in aeroacoustics and hydroacoustics. This noise can be predicted using semi-analytical models that require input measurements of the incoming turbulent flow parameters. However, the turbulence parameters are inherently difficult to measure accurately. These parameters, which include the turbulence kinetic energy and its dissipation rate, have a stochastic nature. This study aims to investigate how small variations in the measurements of turbulence parameters affect the uncertainty of the predicted airfoil–turbulence interaction noise. This is achieved by applying polynomial chaos expansion (PCE) to the semi-analytical model of Amiet’s theory for airfoil-interaction noise. The validity of the deterministic and stochastic simulations is ensured by comparisons against available experimental data from the literature, and Monte Carlo simulations, respectively. Uncertainty quantification is then performed using a stochastic collocation technique, where the aerodynamic noise is evaluated at specific collocation points to estimate the coefficients required for PCE. Both the individual and combined effects of varying the uncertain input turbulence parameters are simulated to quantify the uncertainty of the output aerodynamic noise. The insights gained from the results suggest it is important to incorporate the stochastic behavior of the incoming turbulent flow in operational models for airfoil–turbulence interaction noise predictions. </jats:p>
dc.language	English
dc.publisher	American Institute of Aeronautics and Astronautics
dc.relation.ispartof	AIAA student journal. American Institute of Aeronautics and Astronautics
dc.relation.isbasedon	10.2514/1.J062941
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Uncertainty Analysis in Airfoil–Turbulence Interaction Noise Using Polynomial Chaos Expansion
dc.type	Journal Article
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.date.updated	2024-02-06T00:02:48Z
pubs.publication-status	Published online

Abstract:

Airfoil–turbulence interaction noise is a known source of environmental disturbance and acoustic performance loss in aeroacoustics and hydroacoustics. This noise can be predicted using semi-analytical models that require input measurements of the incoming turbulent flow parameters. However, the turbulence parameters are inherently difficult to measure accurately. These parameters, which include the turbulence kinetic energy and its dissipation rate, have a stochastic nature. This study aims to investigate how small variations in the measurements of turbulence parameters affect the uncertainty of the predicted airfoil–turbulence interaction noise. This is achieved by applying polynomial chaos expansion (PCE) to the semi-analytical model of Amiet’s theory for airfoil-interaction noise. The validity of the deterministic and stochastic simulations is ensured by comparisons against available experimental data from the literature, and Monte Carlo simulations, respectively. Uncertainty quantification is then performed using a stochastic collocation technique, where the aerodynamic noise is evaluated at specific collocation points to estimate the coefficients required for PCE. Both the individual and combined effects of varying the uncertain input turbulence parameters are simulated to quantify the uncertainty of the output aerodynamic noise. The insights gained from the results suggest it is important to incorporate the stochastic behavior of the incoming turbulent flow in operational models for airfoil–turbulence interaction noise predictions.

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http://hdl.handle.net/10453/175332