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Fan noise predictions using scale-resolved, statistical, stochastic and semi-analytical models

Schram, Christophe F. and Christophe, Julien and Shur, Michael and Strelets, Michael and Travin, Andrey and Wohlbrandt, Attila M. and Ewert, Roland and Guérin, Sébastien and Martinez-Lera, Paula and Tournour, Michel and François, Benjamin and Roger, Michel (2017) Fan noise predictions using scale-resolved, statistical, stochastic and semi-analytical models. In: AIAA JOURNAL, p. 3386. 23rd AIAA/CEAS Aeroacoustics Conference, 5.-9. Juni 2017, Denver, Colorado. DOI: 10.2514/6.2017-3386

Full text not available from this repository.

Official URL: http://dx.doi.org/10.2514/6.2017-3386

Abstract

The recently concluded EC FP7 IDEALVENT project has seen the application of a variety of simulation methods by the consortium partners to an industrial blower unit such as used in aircraft Environmental Control Systems. The blower was subjected to different inflow conditions in order to better comprehend the importance of installation effects, and assess the capabilities of the proposed numerical tools to quantify those effects. The prediction tools include scale-resolved, statistical, stochastic and semi-analytical approaches. The predicted acoustic fields were validated by comparison with experimental data obtained on a dedicated test rig, permitting the necessary decontamination of the microphone signals from the reflections at the duct terminations, and turbulent boudary layer related pseudo-sound. A quite good agreement was found between the predicted and measured acoustic data. The tools showed also a good potential for estimating installation effects. Finally, the paper demonstrates the benefits of applying different methods, characterized by different modelling assumptions, for a more thorough understanding of the sound generation mechanisms.

Item URL in elib:https://elib.dlr.de/116006/
Document Type:Conference or Workshop Item (Speech)
Title:Fan noise predictions using scale-resolved, statistical, stochastic and semi-analytical models
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schram, Christophe F.von Karman Institute for Fluid DynamicsUNSPECIFIED
Christophe, Julienvon Karman Institute for Fluid DynamicsUNSPECIFIED
Shur, MichaelSaint Petersburg Polytechnic University and New Technologies & Services, LLCUNSPECIFIED
Strelets, MichaelSaint Petersburg Polytechnic University and New Technologies & Services, LLCUNSPECIFIED
Travin, AndreySaint Petersburg Polytechnic University and New Technologies & Services, LLCUNSPECIFIED
Wohlbrandt, Attila M.attila.wohlbrandt (at) dlr.dehttps://orcid.org/0000-0001-6476-3451
Ewert, Rolandroland.ewert (at) dlr.deUNSPECIFIED
Guérin, Sébastiensebastien.guerin (at) dlr.deUNSPECIFIED
Martinez-Lera, PaulaSiemens Industry SoftwareUNSPECIFIED
Tournour, MichelSiemens Industry SoftwareUNSPECIFIED
François, BenjaminEcole Central de LyonUNSPECIFIED
Roger, MichelEcole Central de LyonUNSPECIFIED
Date:June 2017
Journal or Publication Title:AIAA JOURNAL
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:Yes
DOI :10.2514/6.2017-3386
Page Range:p. 3386
Status:Published
Keywords:industrial blower, Simulation, inflow distortion, broadband noise, acoustic, prediction
Event Title:23rd AIAA/CEAS Aeroacoustics Conference
Event Location:Denver, Colorado
Event Type:international Conference
Event Dates:5.-9. Juni 2017
Organizer:American Institute of Aeroacoustics and Aeronautics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Simulation and Validation
Location: Berlin-Charlottenburg , Braunschweig
Institutes and Institutions:Institute of Propulsion Technology > Engine Acoustic
Institute for Aerodynamics and Flow Technology > Technical Acoustics
Deposited By: Wohlbrandt, Attila
Deposited On:28 Nov 2017 14:53
Last Modified:07 Feb 2018 15:58

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