JAXA Supercomputer System Annual Report April 2018-March 2019

Report Number: R18EA3203

Subject Category: Aeronautical Technology

PDF available here

• Responsible Representative: Shigeru Hamamoto, Aerodynamics Research Unit, Aeronautical Technology Directorate
• Contact Information: Kazuyuki Nakakita, Aerodynamics Research Unit, Aeronautical Technology Directorate(nakakita@chofu.jaxa.jp)
• Members: Kazuyuki Nakakita, Shunsuke Koike, Shigeru Kuchiishi, Kanako Yasue, Hiroshi Kato, Mitsuhiro Murayama, Kentaro Tanaka, Tohru Hirai, Yasushi Ito, Keita Hatanaka, Hiroya Toriida

Abstract

The Aerodynamic Prediction Technology, which is a part of the Innovation for Design, Data-acquisition, Trouble-shoot and Certification in Aircraft Development, constructs the assist technologies to accelerate domestic aircraft development sequences using basic aerodynamic technologies. The target of the Aerodynamic Prediction Technology is paradigm shift from artisanal prediction to analytical one to accelerate domestic aircraft development sequences. This research aims to develop a computational fluid dynamics (CFD) method for simulating the effect of aerodynamic devices, such as vortex generators (VGs), to predict the effect of the aerodynamic devices on real aircraft.

Reference URL

Please refer to ‘Applied fundamental technology | Science & Basic Tech. – Aeronautical Science and Basic Technology Research | Aeronautical Technology Directorate‘.

Reasons for using JSS2

Computational simulations using the JSS2 reveal detailed physical phenomena of the aerodynamic devices, which is difficult only with wind tunnel tests, and enable to improve the design of the devices.

Achievements of the Year

CFD simulations with the TAS code were conducted for JAXA’s high-lift wing noise research model, OTOMO2, with and without vortex generators (VGs). The automatic local remeshing method of an unstructured grid generator, MEGG3D, enabled us to conduct an efficient parametric study of VG locations on the flap. Vortices from VGs placed on the flap interact with the boundary layer on it, suppress boundary layer separation, and improve the flap performance (Fig. 1).

Fig.1: Skin-friction distributions and surface streamlines: (a) baseline configuration; (b) Configuration with eight VGs placed at 15% chord locations

Publications

– Peer-reviewed papers

1) Namura, N., Shimoyama, K., Obayashi, S., Ito, Y., Koike, S., and Nakakita, K., “Multipoint Design Optimization of Vortex Generators on Transonic Swept Wings,” Journal of Aircraft, accepted for publication.

– Non peer-reviewed papers

1) Koike, S., Ito, Y., Murayama, M., Nakakita, K., Yamamoto, K., and Kusunose, K., “Experimental Investigation of Vertical Stabilizer with Vortex Generators and Dorsal Fin,” AIAA Paper 2018-3180, 2018 Applied Aerodynamics Conference, Atlanta, GA, June 2018, DOI: 10.2514/6.2018-3180.

2) Ito, Y., Murayama, M., Koike, S., Yamamoto, K., Nakakita, K., and Kusunose, K., “Computational Investigation of Vertical Stabilizer with Vortex Generators and Dorsal Fin,” AIAA Paper 2018-3530, 2018 Flow Control Conference, Atlanta, GA, June 2018, DOI: 10.2514/6.2018-3530.

Usage of JSS2

Computational Information

• Process Parallelization Methods: MPI
• Thread Parallelization Methods: OpenMP
• Number of Processes: 216 – 324
• Elapsed Time per Case: 24 Hour(s)

Resources Used

Fraction of Usage in Total Resources*1(%): 1.21

Details

Please refer to System Configuration of JSS2 for the system configuration and major specifications of JSS2.

*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.

JAXA Supercomputer System Annual Report April 2018-March 2019