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Computational aero-acoustics (CAA) for aircraft noise prediction - part B

Computational aero-acoustics (CAA) for aircraft noise prediction - part B
Computational aero-acoustics (CAA) for aircraft noise prediction - part B
A symposium on the subject of ‘Computational Aero-Acoustics (CAA) for Aircraft Noise Prediction’ was held at Chilworth Manor near Southampton in March 2010. It was hosted by the Institute of Sound and Vibration Research (ISVR) under the aegis of the International Union of Theoretical and Applied Mechanics (IUTAM), and was supported by the Engineering and Physical Sciences Research Council of the United Kingdom, and by Rolls-Royce plc. The objective of the symposium was to bridge the gap between (mainly academic) research in CAA, and its practical application in the design of quiet, fuel-efficient aircraft. Following the symposium, 31 invited presentations were published as volume 6 of Elsevier's ‘Procedia Engineering’ which can be accessed directly at www.sciencedirect.com. The 13 articles which are presented in this special section of the Journal of Sound and Vibration are edited and peer reviewed versions of a selection of the symposium presentations.

Reducing noise and emissions of commercial aircraft while improving overall fuel efficiency is the most pressing objective for commercial aviation. It is embedded in the ‘Strategic Research Agenda’ (SRA) of the Advisory Council for Aeronautic Research in Europe (ACARE see www.acare4europe.com) and is echoed in the agenda of the Committee on Aviation Environmental Protection (CAEP) within the International Civil Aviation Organisation (ICAO). There is widespread agreement between industry and governments that the only way to manage the future growth of civil aviation towards an environmentally sustainable path is to adopt a ‘balanced approach’ in which technology is developed to improve air quality, reduce carbon emissions and reduce noise simultaneously. In Europe, a 10 dB noise reduction target has been set by ACARE for new aircraft in 2020 compared to a notional 2000 ‘baseline’ level. This requires an order of magnitude decrease in radiated sound power per aircraft at noise certification points. It brings into sharp focus the need for improved noise prediction methods to reduce current industry dependence on physical testing. Such tests are hugely expensive and in practice can only be used to validate proposed designs rather than to explore new design spaces. Improved and validated CAA prediction methods that can be applied with confidence to new configurations within timescales which are acceptable to industry (simulations that run in hours rather than weeks) are urgently needed.

The articles in this special section will be presented in two groups. Six articles are published in this issue (doi numbers: 10.1016/j.jsv.2011.04.013; 10.1016/j.jsv.2011.03.022; 10.1016/j.jsv.2011.03.011; 10.1016/j.jsv.2011.03.009; 10.1016/j.jsv.2011.02.008; and 10.1016/j.jsv.2011.02.005). These deal with CAA models for the generation of turbomachinery noise and its propagation to the far field.

A second group of seven articles will be published in a following issue (doi numbers: 10.1016/j.jsv.2011.04.018; 10.1016/j.jsv.2011.04.014; 10.1016/j.jsv.2011.03.012; 10.1016/j.jsv.2011.02.013; 10.1016/j.jsv.2011.02.010; 10.1016/j.jsv.2011.02.009; and 10.1016/j.jsv.2011.02.007). These focus on CAA application to jet mixing and airframe noise and will be discussed separately at that time.

In this issue, the first three papers deal with CAA models for rotor/stator interaction noise and trailing edge noise, major contributors to turbomachinery noise. Atassi and Logue demonstrate the effectiveness of three-dimensional linear inviscid models for rotor/stator interaction noise. They indicate also that linear cascade models which are commonly used for this purpose are not adequate. Hixon and Sescu describe a new method for imposing acoustics-free vortical disturbances into a nonlinear, inviscid time-accurate CAA calculation for wake/stator interaction noise. The method is validated for an idealised test problem as a necessary step towards its application to realistic configurations. Sandberg and Lloyd present models for broadband trailing edge noise on airfoils or blades. Direct Numerical Simulation (DNS) is used to model a serrated trailing edge. Computations can be performed only for a relatively low Reynolds number, but reveal feedback and noise generation mechanisms which are likely to persist in more realistic flows.

The last three papers in the current issue deal with linearised Euler models for propagation through intake and bypass ducts. Astley et al. review CAA propagation models for such problems, and present Finite Element, frequency domain, CAA predictions for a lined intake. These are sufficiently fast in execution to be used for intake liner optimisation when an axisymmetric geometry is assumed. Ozyoruk and Tester use an alternative frequency domain formulation based on a structured, high order finite difference approach. They show good convergence with measured flow rig data for exhaust ducts. Richter et al. discuss a time-domain, high order, structured method and review the treatment of acoustically absorbing boundary conditions in the time-domain.

The general conclusion which can be drawn from the above articles is that in the case of tone source and propagation models for fan noise, the discipline of CAA is relatively advanced, and indeed close to being suitable for robust application in engine design. The same conclusion does not necessarily hold for jet and airframe noise where turbulent unsteady phenomena are involved. This will be discussed further in the preface to the following issue where articles on these applications are presented
0022-460X
4081-4082
Astley, R.J.
cb7fed9f-a96a-4b58-8939-6db1010f9893
Gabard, G.
bfd82aee-20f2-4e2c-ad92-087dc8ff6ce7
Astley, R.J.
cb7fed9f-a96a-4b58-8939-6db1010f9893
Gabard, G.
bfd82aee-20f2-4e2c-ad92-087dc8ff6ce7

Astley, R.J. and Gabard, G. (2011) Computational aero-acoustics (CAA) for aircraft noise prediction - part B. Journal of Sound and Vibration, 330 (17), 4081-4082. (doi:10.1016/j.jsv.2011.05.005).

Record type: Article

Abstract

A symposium on the subject of ‘Computational Aero-Acoustics (CAA) for Aircraft Noise Prediction’ was held at Chilworth Manor near Southampton in March 2010. It was hosted by the Institute of Sound and Vibration Research (ISVR) under the aegis of the International Union of Theoretical and Applied Mechanics (IUTAM), and was supported by the Engineering and Physical Sciences Research Council of the United Kingdom, and by Rolls-Royce plc. The objective of the symposium was to bridge the gap between (mainly academic) research in CAA, and its practical application in the design of quiet, fuel-efficient aircraft. Following the symposium, 31 invited presentations were published as volume 6 of Elsevier's ‘Procedia Engineering’ which can be accessed directly at www.sciencedirect.com. The 13 articles which are presented in this special section of the Journal of Sound and Vibration are edited and peer reviewed versions of a selection of the symposium presentations.

Reducing noise and emissions of commercial aircraft while improving overall fuel efficiency is the most pressing objective for commercial aviation. It is embedded in the ‘Strategic Research Agenda’ (SRA) of the Advisory Council for Aeronautic Research in Europe (ACARE see www.acare4europe.com) and is echoed in the agenda of the Committee on Aviation Environmental Protection (CAEP) within the International Civil Aviation Organisation (ICAO). There is widespread agreement between industry and governments that the only way to manage the future growth of civil aviation towards an environmentally sustainable path is to adopt a ‘balanced approach’ in which technology is developed to improve air quality, reduce carbon emissions and reduce noise simultaneously. In Europe, a 10 dB noise reduction target has been set by ACARE for new aircraft in 2020 compared to a notional 2000 ‘baseline’ level. This requires an order of magnitude decrease in radiated sound power per aircraft at noise certification points. It brings into sharp focus the need for improved noise prediction methods to reduce current industry dependence on physical testing. Such tests are hugely expensive and in practice can only be used to validate proposed designs rather than to explore new design spaces. Improved and validated CAA prediction methods that can be applied with confidence to new configurations within timescales which are acceptable to industry (simulations that run in hours rather than weeks) are urgently needed.

The articles in this special section will be presented in two groups. Six articles are published in this issue (doi numbers: 10.1016/j.jsv.2011.04.013; 10.1016/j.jsv.2011.03.022; 10.1016/j.jsv.2011.03.011; 10.1016/j.jsv.2011.03.009; 10.1016/j.jsv.2011.02.008; and 10.1016/j.jsv.2011.02.005). These deal with CAA models for the generation of turbomachinery noise and its propagation to the far field.

A second group of seven articles will be published in a following issue (doi numbers: 10.1016/j.jsv.2011.04.018; 10.1016/j.jsv.2011.04.014; 10.1016/j.jsv.2011.03.012; 10.1016/j.jsv.2011.02.013; 10.1016/j.jsv.2011.02.010; 10.1016/j.jsv.2011.02.009; and 10.1016/j.jsv.2011.02.007). These focus on CAA application to jet mixing and airframe noise and will be discussed separately at that time.

In this issue, the first three papers deal with CAA models for rotor/stator interaction noise and trailing edge noise, major contributors to turbomachinery noise. Atassi and Logue demonstrate the effectiveness of three-dimensional linear inviscid models for rotor/stator interaction noise. They indicate also that linear cascade models which are commonly used for this purpose are not adequate. Hixon and Sescu describe a new method for imposing acoustics-free vortical disturbances into a nonlinear, inviscid time-accurate CAA calculation for wake/stator interaction noise. The method is validated for an idealised test problem as a necessary step towards its application to realistic configurations. Sandberg and Lloyd present models for broadband trailing edge noise on airfoils or blades. Direct Numerical Simulation (DNS) is used to model a serrated trailing edge. Computations can be performed only for a relatively low Reynolds number, but reveal feedback and noise generation mechanisms which are likely to persist in more realistic flows.

The last three papers in the current issue deal with linearised Euler models for propagation through intake and bypass ducts. Astley et al. review CAA propagation models for such problems, and present Finite Element, frequency domain, CAA predictions for a lined intake. These are sufficiently fast in execution to be used for intake liner optimisation when an axisymmetric geometry is assumed. Ozyoruk and Tester use an alternative frequency domain formulation based on a structured, high order finite difference approach. They show good convergence with measured flow rig data for exhaust ducts. Richter et al. discuss a time-domain, high order, structured method and review the treatment of acoustically absorbing boundary conditions in the time-domain.

The general conclusion which can be drawn from the above articles is that in the case of tone source and propagation models for fan noise, the discipline of CAA is relatively advanced, and indeed close to being suitable for robust application in engine design. The same conclusion does not necessarily hold for jet and airframe noise where turbulent unsteady phenomena are involved. This will be discussed further in the preface to the following issue where articles on these applications are presented

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More information

e-pub ahead of print date: 19 May 2011
Published date: 15 August 2011
Additional Information: Preface to Special Section on CAA for aircraft noise prediction. Selected peer reviewed presentations from an IUTAM symposium held in Southampton March 2010
Organisations: Inst. Sound & Vibration Research

Identifiers

Local EPrints ID: 300920
URI: http://eprints.soton.ac.uk/id/eprint/300920
ISSN: 0022-460X
PURE UUID: e0068d74-67f3-4280-ba4c-936dd6ad4dfe

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Date deposited: 01 Mar 2012 11:49
Last modified: 14 Mar 2024 10:26

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Author: R.J. Astley
Author: G. Gabard

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