Prediction of Aeroelasticity of Rotor blades
JAXA Supercomputer System Annual Report February 2022-January 2023
Report Number: R22EDA102C21
Subject Category: Aeronautical Technology
- Responsible Representative: Arizono Hitoshi, Aeronautical Technology Directorate, Aviation Environmental Sustainability Innovation Hub
- Contact Information: Hideaki Sugawara(sugawara.hideaki@jaxa.jp)
- Members: Hideaki Sugawara, Yasutada Tanabe, Keita Kimura
Abstract
The aeroelasticity of rotor blades affects the aerodynamic performance of the rotor. The prediction technologies for aeroelastic deformation of the rotor blade are important for rotorcraft design. The objective is to establish and validate simulation technologies for the aeroelastic analysis of the rotor. The rotorcraft community is conducting an international workshop. A wind tunnel test will be conducted, and numerous experimental data will be measured in various flight conditions. Numerical results will be validated with the experimental data and compared with other organizations in the international workshop. A preliminary analysis of the wind tunnel test is performed this year, and the test conditions are discussed.
Reference URL
N/A
Reasons and benefits of using JAXA Supercomputer System
Computational resources and computational capability are required to perform many numerical simulations.
Achievements of the Year
Numerical simulations are performed in hover, high-speed forward flight, descent flight, high load, and high advance ratio conditions (Fig. 1). The simulation results are compared with other organizations, and the test conditions are discussed based on the results. The prediction results by the rotorcraft CFD tool, rFlow3D, developed at JAXA show good correlations.
Publications
– Oral Presentations
van der Wall, B. G., Lim, J. W., Riemenschneider, J., Kalow, S., Wilke, G. A., Boyd, D. D., Bailly, J., Delrieux, Y., Cafarelli, I., Tanabe, Y., Sugawara, H., Jung, S., N., Kim, D, Kang, H, J., Barakos, G., Steininger, R., “Smart Twisting Active Rotor (STAR) – Pre-Test Predictions,”, 48th European Rotorcraft Forum, 2022.
Usage of JSS
Computational Information
- Process Parallelization Methods: N/A
- Thread Parallelization Methods: OpenMP
- Number of Processes: 1
- Elapsed Time per Case: 336 Hour(s)
JSS3 Resources Used
Fraction of Usage in Total Resources*1(%): 0.39
Details
Please refer to System Configuration of JSS3 for the system configuration and major specifications of JSS3.
System Name | CPU Resources Used(Core x Hours) | Fraction of Usage*2(%) |
---|---|---|
TOKI-SORA | 949631.27 | 0.04 |
TOKI-ST | 2534825.16 | 2.53 |
TOKI-GP | 0.00 | 0.00 |
TOKI-XM | 0.00 | 0.00 |
TOKI-LM | 0.00 | 0.00 |
TOKI-TST | 262929.80 | 6.93 |
TOKI-TGP | 0.00 | 0.00 |
TOKI-TLM | 0.00 | 0.00 |
File System Name | Storage Assigned(GiB) | Fraction of Usage*2(%) |
---|---|---|
/home | 60.70 | 0.05 |
/data and /data2 | 4210.73 | 0.03 |
/ssd | 621.46 | 0.09 |
Archiver Name | Storage Used(TiB) | Fraction of Usage*2(%) |
---|---|---|
J-SPACE | 0.00 | 0.00 |
*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 Used(Hours) | Fraction of Usage*2(%) | |
---|---|---|
ISV Software Licenses(Total) | 26.10 | 0.02 |
*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.
JAXA Supercomputer System Annual Report February 2022-January 2023