Research on Aircraft Multidisciplinary Design Technology

JAXA Supercomputer System Annual Report February 2022-January 2023

Report Number: R22EA0602

Subject Category: Aeronautical Technology

Responsible Representative: Dongyoun Kwak, Aviation Technology Directorate, Aviation Enviromental Sustanability Innovation Hub
Contact Information: Mitsuhiro Murayama, Aviation Technology Directorate, Aviation Environmental Sustainability Innovation Hub(murayama.mitsuhiro@jaxa.jp)
Members: Ryutaro Furuya, Tohru Hirai, Tomoaki Ikeda, Yasushi Ito, Fumitake Kuroda, Keisuke Ohira, Junichi Kazawa, Dongyoun Kwak, Mitsuhiro Murayama, Kentaro Tanaka, Kuniyuki Takekawa

Abstract

The purpose of the research is to develop and mature a bunch of advanced and innovative elemental technologies on aerodynamics, aeroacoustics, and structures to enable airframe design with higher environmental performances of future aircraft application, thereby helping the Japanese aviation industry to enhance its share on the global market.

Reference URL

N/A

Reasons and benefits of using JAXA Supercomputer System

To develop and mature advanced and innovative technologies of aerodynamic drag reduction, aircraft noise reduction, and airframe-engine installation design for future aircrafts, development of CFD technologies and CFD-based design/analyis have been conducted in this research. The high-fidelity CFD analysis of the whole aircraft configurations with the airframe-engine installation requires large computational resources. JSS enables the high-fidelity evaluations of the peformance in a timely manner and the technology developments.

Achievements of the Year

Studes on airframe-engine installation design for low-noise JAXA Technology-Reference-Aircraft 2035A (TRA2035A, 220-seat class) with a wide fuselage have been conducted by steady-state RANS CFD analyses. The changes of drag and performances by installing short inlet nacelles and BLI nacellesa have been clarified in the studies. Figure 1 shows TRA2035A configuration used in the studies. In addition, CFD prediction accuracy of drag and pitching moment near the condition of buffet have been validated in CFD Drag Prediction Workshop.

Fig.1: JAXA Low-noise Technology-Reference-Aircraft 2035A (TRA2035A, 220-seat class) with a wide fuselage

Publications

– Oral Presentations

Murayama, M., Ito, Y. and Furuya, R., “JAXA’s TAS Code Results for the 7th AIAA CFD Drag Prediction Workshop,” 7th AIAA CFD Drag Prediction Workshop, 2022.

Usage of JSS

Computational Information

Process Parallelization Methods: MPI
Thread Parallelization Methods: OpenMP
Number of Processes: 100 – 648
Elapsed Time per Case: 10 Hour(s)

JSS3 Resources Used

Fraction of Usage in Total Resources*1(%): 0.75

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	20356700.92	0.89
TOKI-ST	25288.37	0.03
TOKI-GP	0.00	0.00
TOKI-XM	0.00	0.00
TOKI-LM	3701.17	0.25
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	175.71	0.16
/data and /data2	11642.43	0.09
/ssd	3466.07	0.48

Archiver Resources
Archiver Name	Storage Used (TiB)	Fraction of Usage*2(%)
J-SPACE	76.08	0.34

*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)	44.38	0.03

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