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Innovation for Design, Data-acquisition, Trouble-shoot and Certification in Aircraft Development: Aerodynamic Optimization

JAXA Supercomputer System Annual Report April 2017-March 2018

Report Number: R17EA3202

Subject Category: Aeronautical Technology

PDF available here

  • Responsible Representative: Takeshi Ito, Aeronautical Technology Directorate, Next Generation Aeronautical Innovation Hub Center
  • Contact Information: Shigeru Kuchi-Ishi shigeruk@chofu.jaxa.jp
  • Members: Shigeru Kuchiishi, Takashi Ishida, Atsushi Hashimoto, Masahiro Kanazaki, Suzuki Kohji, Takatoshi Nakayama, Minoru Yoshimoto, Shinsuke Nishimura, Yukinori Morita, Takuya Ogura, Kazufumi Uwatoko

Abstract

An aerodynamic optimization tool using the unstructured CFD code FaSTAR is develped and its validity and efficiency are examined. A Multi-Objective Evolutionary Algorithm (MOEA) is employed as an aerodynamic optimization method. This tool is aimed to enable the direct evolutionary computing to perform within a practical computational time by utilizing the high speed performance of FaSTAR. In the present project, basic programs are developed and validated using JSS2.

Reference URL

N/A

Reasons for using JSS2

Aerodynamic optimization using an evolutionary algorithm requires a number of high-fidelity and large-scaled computations (3D RANS analysis) and needs to use the supercomputer.

Achievements of the Year

For the Multi-Objective Evlutionary Algorithm (MOEA), the program was extended to the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) that enables to produce more equable and diversified parate-optimal solutions. Also the directed mating algorithm was introduced to enhance robustness of the program for problems including constraint conditions. The program was applied to a constrained optimization problem for the NASA Common Research Model (CRM) and it was found that the present program can produce optimal solutions more effectively compared to the foregoing program.

Annual Reoprt Figures for 2017

Fig.1: NASA CRM airfoil optimization result

 

Annual Reoprt Figures for 2017

Fig.2: Comparison of the optimal solution convergence history

 

Publications

■ Presentations

1) Kanazaki, M., Kuchi-Ishi, S., and Suzuki K., ``Development of an Aerodynamic Optimization Library by Evolutionary Algorithm,'' FaSTAR User's Conference, Akihabara Convention Hall, 2017.

Usage of JSS2

Computational Information

  • Process Parallelization Methods: MPI
  • Thread Parallelization Methods: N/A
  • Number of Processes: 96 - 512
  • Elapsed Time per Case: 240.00 hours

Resources Used

 

Fraction of Usage in Total Resources*1(%): 0.10

 

Details

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

Computational Resources
System Name Amount of Core Time
(core x hours)
Fraction of Usage*2(%)
SORA-MA 356,995.84 0.05
SORA-PP 55,829.90 0.70
SORA-LM 0.02 0.00
SORA-TPP 0.00 0.00

 

File System Resources
File System Name Storage Assigned
(GiB)
Fraction of Usage*2(%)
/home 587.53 0.41
/data 24,481.17 0.45
/ltmp 8,646.34 0.65

 

Archiver Resources
Archiver Name Storage Used
(TiB)
Fraction of Usage*2(%)
J-SPACE 0.32 0.01

*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 2017-March 2018


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Language / 言語

"Annual Report" available

How to use JSS3

To use JSS3, please refer to "How to use JSS3" page .

Location

Chofu Aerospace Center
7-44-1 Jindaiji Higashi-machi, Chofu-shi, Tokyo