本文へ移動

サイトナビゲーションへ移動

検索ボックスへ移動

サイドバーへ移動

ここは、本文エリアの先頭です。

Aerodynamic Simulations on Airframe Noise Reduction Technology (FQUROH-2)

JAXA Supercomputer System Annual Report February 2022-January 2023

Report Number: R22EDA101R20

Subject Category: Aeronautical Technology

PDF available here

  • Responsible Representative: Takashi Aoyama, Program Director of Aviation Technology, Aviation Technology Directorate
  • Contact Information: Takehisa Takaishi, FQUROH-2 Pre-Project Team (Airframe Noise Reduction Technology Pre-Project Team), Aviation Technology Directorate(takaishi.takehisa@jaxa.jp)
  • Members: Takehisa Takaishi, Mitsuhiro Murayama, Yasushi Ito, Ryotaro Sakai, Kazuomi Yamamoto, Kazuki Fukaya, Kentaro Tanaka, Tohru Hirai, Gen Nakano, Takashi Ishida

Abstract

In order to meet the projected demand for air passengers, and to strengthen the international competitiveness of Japan airports and improve the convenience of passengers, major airports are considering increasing the number of takeoffs and landings. The maturity of the technology for the reduction of airframe noise generated at high-lift devices and landing gear needs to be increased to achieve noise reduction in areas surrounding airports even with the expected increased number of takeoffs and landings. In this project, we have been developing a flight test plan using a commercial airplane that demonstrates the reduction of airframe noise as part of activities aimed at practical development of the airframe noise reduction technology. Computational simulations have been utilized to verify the feasibility of practical noise reduction concepts and design methods. This computational activity focuses on the evaluation of noise reduction concepts applied to an airplane by exploring their aerodynamic impacts to the performance of the airplane.

Reference URL

Please refer to http://www.aero.jaxa.jp/eng/research/ecat/fquroh/ .

Reasons and benefits of using JAXA Supercomputer System

The JSS3 enabled a large number of high-fidelity Reynolds-averaged Navier-Stokes (RANS) simulations with aerodynamically-important details in several flight configurations in the expected flight envelop to be conducted in a timely manner. The aerodynamic effect of low-noise devices can be evaluated and quantified, which is difficult to obtain only with wind tunnel tests.

Achievements of the Year

In addition to demonstrating noise reduction concepts applied to a commercial airplane in a flight test, the same noise reduction concepts will be applied to a common high-lift research model (CRM-HL) to evaluate their generality in this research project. Reynolds averaged Navier-Stokes (RANS) simulations have been conducted for the design of high-lift device layout of a wind tunnel model of the CRM-HL. In-tunnel simulations have also been conducted to understand the flow around the CRM-HL in a wind tunnel to set basic specifications of the wind tunnel model.

Annual Reoprt Figures for 2022

Fig.1: Computational grid for in-tunnel RANS simulations to check feasibility of far-field noise measurements

 

Publications

– Peer-reviewed papers

Ito, Y., Murayama, M., Yokokawa, Y., Yamamoto, K., Tanaka, K., and Hirai, T., “Wind Tunnel Installation Effects on Japan Aerospace Exploration Agency’s Standard Model,” Journal of Aircraft, Vol. 59, No. 5, September 2022, pp. 1281-1302, DOI: 10.2514/1.C036741.

Usage of JSS

Computational Information

  • Process Parallelization Methods: MPI
  • Thread Parallelization Methods: OpenMP
  • Number of Processes: 128 – 600
  • Elapsed Time per Case: 11.3 Hour(s)

JSS3 Resources Used

 

Fraction of Usage in Total Resources*1(%): 0.19

 

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 5080147.91 0.22
TOKI-ST 6576.02 0.01
TOKI-GP 0.00 0.00
TOKI-XM 0.00 0.00
TOKI-LM 0.00 0.00
TOKI-TST 0.00 0.00
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 55.13 0.05
/data and /data2 6206.35 0.05
/ssd 496.59 0.07

 

Archiver Resources
Archiver Name Storage Used
(TiB)
Fraction of Usage*2(%)
J-SPACE 466.64 2.07

*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)
348.75 0.24

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

JAXA Supercomputer System Annual Report February 2022-January 2023