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Acoustic Liner Program for High-bypass-ratio Aircraft engines (acoustic performance improvement)

JAXA Supercomputer System Annual Report February 2022-January 2023

Report Number: R22EDA101C75

Subject Category: Aeronautical Technology

PDF available here

  • Responsible Representative: Kenichiro NAGAI, Aeronautical Technology Directorate, Aviation Environmental Sustainability Innovation Hub
  • Contact Information: Shunji ENOMOTO(enomoto.shunji@jaxa.jp)
  • Members: Shunji ENOMOTO , Hideshi OINUMA , Kenichiro NAGAI , Junichi OKI , Gai KUBO , Tatsuya ISHII

Abstract

Ultra high bypass ratio aviation jet engines have a smaller sound absorbing liner area than conventional engines. In this project, we will develop sound-absorbing device technology that provides high noise reduction performance even with a small-sized sound-absorbing liner.

Reference URL

N/A

Reasons and benefits of using JAXA Supercomputer System

To perform many LES calculations by changing the shape of the sound absorbing liner, the calculation performance and the storage capacity of JAXA supercomputer system were required.

Achievements of the Year

In this study, the impulse response method is used to numerically simulate phenomena that occur when sound is incident on a sound-absorbing liner used to reduce noise in aircraft jet engines. This year, we showed that by dividing the impulse response into two parts, it is possible to consider the actual phenomenon as the sum of the two phenomena. Figure 1 shows an example of impulse response splitting by numerical simulation using the impulse response method. The upper panel shows the sound pressure when an impulse travels through a flow duct with an acoustic liner. The middle panel shows the sound pressure when an impulse is applied to a flow duct without an acoustic liner. The lower panel is the upper panel minus the middle panel, and is the sound pressure radiated from the vibration in the acoustic liner. Figure 2 shows the convolution of each of these impulse responses with a sinusoidal wave of resonant frequency. The upper panel shows the sound wave passing through the flow duct with the acoustic liner and the sound becoming quieter. The middle panel shows the incident sound wave and the lower panel shows the sound wave radiated from the acoustic liner. It can be seen that the upper row is the sum of the middle and lower rows. From this, it is confirmed that the resonant acoustic liner emits sound in the opposite phase of the incident sound and muffles it.

Fig.1(video): Impulse response (sound pressure) and its division. Upper: Impulse response of flow duct with acoustic liner. Middle: Impulse response of flow duct without acoustic liner. Bottom: Impulse response radiated from the acoustic liner.

Fig.2(video): Results of convolution of each impulse response (sound pressure). Upper: The effect of the acoustic liner. Middle: Incident sound wave. Bottom: Sound waves radiated from the acoustic liner. It can be confirmed that the sound radiated by the acoustic liner cancels the incident sound.

Publications

– Non peer-reviewed papers

(1) ENOMOTO Shunji, OINUMA Hideshi, NAGAI Kenichiro, OKI Junichi, ISHII Tatsuya, “Evaluation of Acoustic Liner by Numerical Analysis Using Impulse Response Method”, JAXA Special Publication JAXA-SP-22-007, pp.223-236 (in Japanese)

(2) Shunji Enomoto,”Numerical Analysis of Acoustic Liners for Aeroengines Using the Impulse Response Method”, Acoustical Society of Japan, Noise and Vibration Research Meeting Document N -2023-10 (in Japanese)

(3) Shunji ENOMOTO , Hideshi OINUMA , Kenichiro NAGAI , Junichi OKI , Gai KUBO , Tatsuya ISHII, Yo Murata, “Performance Analysis of Acoustic Liner with Fine-Perforated-Film by Numerical Simulation Using Impulse Response Method”, The 2023 AIAA Aviation Forum, (to be presented 2023-06-13)

Usage of JSS

Computational Information

  • Process Parallelization Methods: MPI
  • Thread Parallelization Methods: OpenMP
  • Number of Processes: 2 – 400
  • Elapsed Time per Case: 100 Hour(s)

JSS3 Resources Used

 

Fraction of Usage in Total Resources*1(%): 0.68

 

Details

Please refer to System Configuration of JSS3 for the system configuration and major specifications of JSS3.

Computational Resources
System Name CPU Resources Used
(Core x Hours)
Fraction of Usage*2(%)
TOKI-SORA 17756094.67 0.77
TOKI-ST 111388.33 0.11
TOKI-GP 0.00 0.00
TOKI-XM 0.00 0.00
TOKI-LM 0.00 0.00
TOKI-TST 78494.20 2.07
TOKI-TGP 0.00 0.00
TOKI-TLM 0.00 0.00

 

File System Resources
File System Name Storage Assigned
(GiB)
Fraction of Usage*2(%)
/home 7.69 0.01
/data and /data2 7483.08 0.06
/ssd 393.85 0.05

 

Archiver Resources
Archiver Name Storage Used
(TiB)
Fraction of Usage*2(%)
J-SPACE 20.86 0.09

*1: Fraction of Usage in Total Resources: Weighted average of three resource types (Computing, File System, and Archiver).

*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.

 

ISV Software Licenses Used

ISV Software Licenses Resources
ISV Software Licenses Used
(Hours)
Fraction of Usage*2(%)
ISV Software Licenses
(Total)
414.19 0.29

*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.

JAXA Supercomputer System Annual Report February 2022-January 2023