Physics understanding and modeling based on high-fidelity numerical analysis

JAXA Supercomputer System Annual Report February 2025-January 2026

Report Number: R25EDA201J01

Subject Category: Aeronautical Technology

Responsible Representative: Abe Hiroyuki, Aviation Technology Directrate, Fundamental Aeronautics Research Unit
Contact Information: Abe Hiroyuki(abe.hiroyuki@jaxa.jp)
Members: Hiroyuki Abe, Manabu Hisida, Koetsu Ito, Ryohei Kirihara, Takuhito Kuwabara, Shingo Matsuyama, Taisuke Nambu, Kei Shimura, Hiroki Yao

Abstract

The aim is to model key phenomena of turbulence based on physics understanding by detailed and high-fidelity simulations and to lead the research.

Reference URL

N/A

Reasons and benefits of using JAXA Supercomputer System

World-level research in this field requires massively parallel huge computational resource and only so-called supercomputer system can provide it.

Achievements of the Year

A large-scale DNS (Direct Numerical Simulation) of an oscillating turbulent boundary layer has been performed for examining the effects of adverse and favorable pressure gradients on the turbulent boundary layer. The Reynolds number based on the amplitude of the freestream velocity and the laminar boundary-layer thickness is set to Re_δs = 1800, which is is the world's highest Reynolds number in this configuration. Mean and turbulence statistics such as mean velocity and Reynolds stress have been obtained via a phase averaging.

Fig.1: Isosurfaces of a positive Q (the second-invariant of the deformation tensor) as a vortex indicator at Re_δs = 1800 under an adverse pressure gradient condition.

Publications

- Invited Presentations

H. Abe, "JAXA's CFD and modeling efforts for off-design conditions," NASA High Fidelity CFD Workshop 2025 (Suffolk, VA, May 20-22, 2025).

- Oral Presentations

H. Abe, P.R. Spalart, " Effects of pressure gradients on DNS of an oscillating turbulent boundary layer," American Physical Society 78th Annual Meeting of the APS Division of Fluid Dynamics (Huston, TX, November 23-25, 2025).

Usage of JSS

Computational Information

Process Parallelization Methods: MPI
Thread Parallelization Methods: Automatic Parallelization
Number of Processes: 192 - 640
Elapsed Time per Case: 1000 Hour(s)

JSS3 Resources Used

Fraction of Usage in Total Resources*1(%): 2.52

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	67434174.14	3.06
TOKI-ST	34316.25	0.04
TOKI-GP	0.00	0.00
TOKI-XM	38.98	0.01
TOKI-LM	3276.82	0.25
TOKI-TST	3.22	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	1024.00	1.64
/data and /data2	102400.00	0.67
/ssd	30720.00	1.87

Archiver Resources
Archiver Name	Storage Used (TiB)	Fraction of Usage*2(%)
J-SPACE	61.99	0.19

*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)	776.37	0.54

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