Research and Development on Airframe Noise Reduction Technology (FQUROH-2) #1

JAXA Supercomputer System Annual Report February 2025-January 2026

Report Number: R25ECA10102

Subject Category: Aeronautical Technology

Responsible Representative: Atsushi Kanda, Program Director of Aviation Technology, Aviation Technology Directorate
Contact Information: Takehisa Takaishi, FQUROH-2 Project Team (Airframe Noise Reduction Technology Project Team), Aviation Technology Directorate(takaishi.takehisa@jaxa.jp)
Members: Takehisa Takaishi, Mitsuhiro Murayama, Yasushi Ito, Takashi Ishida, Yoimi Kojima, Kazuomi Yamamoto, Kentaro Tanaka, Tohru Hirai, Gen Nakano, Manabu Hisida

Abstract

Major airports in Japan are considering increasing the number of takeoffs and landings to meet the projected growth in air travel demand, strengthen their international competitiveness, and enhance passenger convenience. To support this expansion, it is essential to advance technologies that reduce airframe noise—particularly noise generated by high-lift devices and landing gear—so that surrounding communities are not adversely affected. Our approach includes developing a flight-test plan using a commercial aircraft to demonstrate airframe-noise reduction under real operating conditions. In parallel, we have created an 8%‑scale semi‑span wind tunnel model based on NASA's High‑Lift Common Research Model (CRM‑HL) to conduct further demonstrations using a generic aircraft configuration. These efforts represent key steps toward the practical development of effective noise-reduction technologies. We also use computational simulations to confirm the feasibility of noise‑reduction concepts and associated design methods. This computational activity serves to evaluate a new advanced large‑scale simulation method currently under development.

Reference URL

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

Reasons and benefits of using JAXA Supercomputer System

The JSS3 has been used to analyze the detailed physics of noise generation and to optimize noise‑reduction designs. The FQUROH-2 project aims to advance the technology maturity of airframe noise‑reduction methods by leveraging advanced, large‑scale, high‑fidelity computational simulations on the JSS3's high‑performance computing platform and by demonstrating these high‑fidelity design technologies through flight tests. Thanks to the computational capabilities of the JSS3, it has become possible to design low‑noise devices based on a detailed understanding of physical phenomena that are difficult to capture solely through wind tunnel testing.

Achievements of the Year

A new method has been implemented in the unstructured solver FaSTAR to enhance the CFD capabilities required for evaluating airframe noise‑reduction technologies. To significantly reduce the computational cost of unsteady flow simulations, the immersed boundary method (IBM) has been implemented. This approach eliminates the need for high‑density meshes in the near‑wall region and simplifies the mesh‑generation process. Verification of the implemented IBM has been carried out, allowing us to identify areas requiring further improvement. In parallel, additional functionalities needed for far‑field noise prediction based on IBM‑based unsteady simulations have been developed. To improve spatial accuracy, a higher‑order formulation of the inviscid fluxes was implemented using gradient information. As part of the functional verification, quasi‑three-dimensional Reynolds‑averaged Navier–Stokes (RANS) simulations were conducted for an airfoil. The results confirmed that accuracy comparable to that of conventional fine‑mesh simulations can be achieved even with relatively coarse meshes. For large‑scale mesh computations, the pre‑ and post‑processing tools were upgraded to handle meshes exceeding the single‑precision integer limit of approximately two billion nodes. Verification with a mesh of about one billion nodes demonstrated that the unsteady data output required for far‑field noise evaluation can be processed without issues.

Publications

N/A

Usage of JSS

Computational Information

Process Parallelization Methods: MPI
Thread Parallelization Methods: N/A
Number of Processes: 1 - 2400
Elapsed Time per Case: 39.5 Hour(s)

JSS3 Resources Used

Fraction of Usage in Total Resources*1(%): 0.01

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	100552.57	0.00
TOKI-ST	7829.41	0.01
TOKI-GP	0.00	0.00
TOKI-XM	0.00	0.00
TOKI-LM	976.61	0.07
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	0.00	0.00
/data and /data2	0.00	0.00
/ssd	0.00	0.00

Archiver Resources
Archiver Name	Storage Used (TiB)	Fraction of Usage*2(%)
J-SPACE	443.60	1.35

*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)	0.00	0.00

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