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Numerical analysis for optimal design of helicopter rotor blades

JAXA Supercomputer System Annual Report February 2022-January 2023

Report Number: R22EDA201C22

Subject Category: Aeronautical Technology

PDF available here

  • Responsible Representative: Hitoshi Arizono,Aeronautical Technology Directorate, Aviation Environmental Sustainability Innovation Hub Aeronautical Technology Directorate
  • Contact Information: Keita Kimura(kimura.keita@jaxa.jp)
  • Members: Fumihiro Kajiwara, Keita Kimura, Masahiko Sugiura, Hideaki Sugawara, Yasutada Tanabe

Abstract

A cooperative study of rotor blade optimization methods is being conducted by JAXA, DLR, and ONERA to validate rotor blade analysis tools and optimization methods, and to accumulate knowledge. In this fiscal year, optimization of the blade shape considering the trade-off between hovering and forward flight performances was conducted. In preparation for the low-noise optimization to be conducted in the next fiscal year, simulations of baseline blade considering elastic deformation was performed and a reasonable deformation profile was obtained. In optimization, the performance of the obtained design solution must be evaluated accurately, and performance evaluation by CFD analysis is important.

Reference URL

N/A

Reasons and benefits of using JAXA Supercomputer System

In CFD-based optimization, a large number of cases with several design variables need to be performed in the CFD analysis, and the use of a supercomputer is essential; DLR/ONERA is conducting a similar HPC-based optimization, and comparison and study using results obtained using a supercomputer is appropriate.

Achievements of the Year

A common rotor blade optimization problem was set up among the three organizations (JAXA-DLR-ONERA), and CFD was used to optimize the shape of the rotor blades. In addition, elastic deformation analysis related to noise performance optimization was conducted, which will be carried out in the following years.

Figure 1 illustrates the lift distribution on the rotor surface of the optimal blade under forward flight conditions. During forward flight, the rotor blades are subjected to asymmetric flow fields on the advancing and retreating sides. The optimized rotor blades share a large lift at the front (180deg) and aft(0deg) of the rotor.

Figure 2 illustrates the tip vortices generated by the blades during forward flight with the helicopter shaft tilted backward and forward. The positional relationship between the blade and vortices changes with the shaft angle, and a greater or lesser blade-vortex mutual interference appears.

Figure 3 shows an overview of the elastic deformation analysis. A coupled analysis of blade flap-lead/lag-twist deformation and aerodynamics is performed. It can be seen that the blade exhibits complex deformation due to the asymmetric flow field on the advancing and retreating sides, as well as the operation at different pitch angles for each azimuth.

Annual Reoprt Figures for 2022

Fig.1: Lift force distribution on rotor surface (CzM2)

 

Annual Reoprt Figures for 2022

Fig.2: Visualization of flow field around rotor during forward flight (alpha: shaft angle)

 

Annual Reoprt Figures for 2022

Fig.3: Schematic of elastic deformation analysis of blades

 

Publications

– Peer-reviewed papers

Wilke, G., Bailly, J., Kimura, K., and Tanabe, Y., “JAXA-ONERA-DLR Cooperation: Results from Rotor Optimization in Hover”, CEAS Aeronautical Journal, Vol. 13, pp. 313-333, April 2022

– Oral Presentations

Kimura, K., Wilke, G., Bailly, J., and Tanabe, Y., “JAXA-ONERA-DLR Cooperation: Results from Rotor Optimization in Forward Flight”, 48th European Rotorcraft Forum, Winterthur, Switzerland, September 2022

Usage of JSS

Computational Information

  • Process Parallelization Methods: N/A
  • Thread Parallelization Methods: OpenMP
  • Number of Processes: 1
  • Elapsed Time per Case: 200 Hour(s)

JSS3 Resources Used

 

Fraction of Usage in Total Resources*1(%): 0.07

 

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 450956.15 0.02
TOKI-ST 379894.87 0.38
TOKI-GP 0.00 0.00
TOKI-XM 0.00 0.00
TOKI-LM 0.00 0.00
TOKI-TST 48049.66 1.27
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 101.66 0.09
/data and /data2 13466.11 0.10
/ssd 654.15 0.09

 

Archiver Resources
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 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.

JAXA Supercomputer System Annual Report February 2022-January 2023