Acoustic optimisation and prediction of sound propagation in turbofan engine ducts
Acoustic optimisation and prediction of sound propagation in turbofan engine ducts
The research presented in this thesis explores the prediction of noise propagation and
radiation in turbofan engine intakes and bypass ducts, and the optimisation of noise attenuation
by using acoustic liners. A commercial FE/IE code ACTRAN/TM is used
within two shell programs; B-induct for bypass ducts and ANPRORAD for intake ducts.
An automated liner impedance capability has been demonstrated by exploiting an optimisation
suite, SOFT.
Automated liner impedance optimisations to maximise the liner insertion loss have
been performed for a uniform bypass duct with a multimodal noise source, by using
B-induct within SOFT. Results show that, multi-segment liners are effective at low frequencies
when few acoustic duct modes are present and less so at high frequencies when
many modes are present. Other results show that, at high frequencies, having different
liner impedances on the inner and outer walls could be more effective than axially segment
liners. An automated liner impedance optimisation has also been performed for a realistic
bypass duct, and an A-weighting has been considered.
Far field noise levels predicted by using ANPRORAD analysis have been validated
against measured data from rig and engine tests. The predicted results are in good agreement
with the measured data when the noise source is calibrated using in-duct measured
values. This demonstrates that ANPRORAD is a viable methodology for intake noise
predictions in industry. ANPRORAD has also been applied to investigate the effect of
the intake geometry on low-frequency acoustic reflections in the intake, and integrated
within SOFT to perform automated liner impedance optimisations to minimise acoustic
reflections to the fan.
Achunche, Iansteel Mukum
c4fb7ed1-013b-44df-8582-b65813e21e5f
January 2010
Achunche, Iansteel Mukum
c4fb7ed1-013b-44df-8582-b65813e21e5f
Astley, R.J.
cb7fed9f-a96a-4b58-8939-6db1010f9893
Kempton, A.J.
b74e92b2-7c9c-4678-890d-824a0b984086
Achunche, Iansteel Mukum
(2010)
Acoustic optimisation and prediction of sound propagation in turbofan engine ducts.
University of Southampton, Institute of Sound and Vibration Research, Doctoral Thesis, 225pp.
Record type:
Thesis
(Doctoral)
Abstract
The research presented in this thesis explores the prediction of noise propagation and
radiation in turbofan engine intakes and bypass ducts, and the optimisation of noise attenuation
by using acoustic liners. A commercial FE/IE code ACTRAN/TM is used
within two shell programs; B-induct for bypass ducts and ANPRORAD for intake ducts.
An automated liner impedance capability has been demonstrated by exploiting an optimisation
suite, SOFT.
Automated liner impedance optimisations to maximise the liner insertion loss have
been performed for a uniform bypass duct with a multimodal noise source, by using
B-induct within SOFT. Results show that, multi-segment liners are effective at low frequencies
when few acoustic duct modes are present and less so at high frequencies when
many modes are present. Other results show that, at high frequencies, having different
liner impedances on the inner and outer walls could be more effective than axially segment
liners. An automated liner impedance optimisation has also been performed for a realistic
bypass duct, and an A-weighting has been considered.
Far field noise levels predicted by using ANPRORAD analysis have been validated
against measured data from rig and engine tests. The predicted results are in good agreement
with the measured data when the noise source is calibrated using in-duct measured
values. This demonstrates that ANPRORAD is a viable methodology for intake noise
predictions in industry. ANPRORAD has also been applied to investigate the effect of
the intake geometry on low-frequency acoustic reflections in the intake, and integrated
within SOFT to perform automated liner impedance optimisations to minimise acoustic
reflections to the fan.
More information
Published date: January 2010
Organisations:
University of Southampton
Identifiers
Local EPrints ID: 162395
URI: http://eprints.soton.ac.uk/id/eprint/162395
PURE UUID: ceba498e-2514-4d6e-b254-b6413fad88a0
Catalogue record
Date deposited: 20 Aug 2010 10:15
Last modified: 14 Mar 2024 02:02
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Contributors
Author:
Iansteel Mukum Achunche
Thesis advisor:
A.J. Kempton
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