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High-Resolution, Efficient CFD Methods by Second Slope Limiter for Transonic Speeds

JAXA Supercomputer System Annual Report April 2018-March 2019

Report Number: R18EDA201N10

Subject Category: Aeronautical Technology

PDF available here

  • Responsible Representative: Takashi Aoyama, Aeronautical Technology Directorate, Numerical Simulation Research Unit
  • Contact Information: Keiichi Kitamura(kitamura@ynu.ac.jp)
  • Members: Atsushi Hashimoto, Keiichi Kitamura, Kanta Fukumoto, Ayano Inatomi, Toshiaki Harada, Suguru Ogawa, Yuya Takagi, Hiroyuki Takimoto, Hiroto Yaginuma, Masashi Kanamori, Naoya Hase, Hayato Kawashima, Yoshikatsu Furusawa, Ryoyu Uematsu, Takeshi Fujimoto

Abstract

A high-resolution, Delayed DES has been conducted around whole the aircraft under the low-speed buffet condition. This numerical case is known as a tough problem, since it is difficult to obtain good numerical solutions that agree well with the corresponding experimental data. In the present study, through extensive investigations of various aspects of CFD schemes (e.g., turbulence models and their coefficients, numerical fluxes, slope limiters), we proposed a zone-based Delayed DES, coined as “HR-SLAU2-DDES”. Then, we successfully obtained better pressure distributions on the main wing than the earlier results.

Reference URL

N/A

Reasons for using JSS2

1) Expensive, unsteady CFD around whole the aircraft; 2) Many numerical cases (aerodynamic problems) in which our proposed schemes are verified.

Achievements of the Year

A high-resolution, Delayed DES has been conducted around whole the aircraft under the low-speed buffet condition. This numerical case is known as a tough problem, since it is difficult to obtain good numerical solutions that agree well with the corresponding experimental data. In the present study, we first proposed a simple dirty-cell detection method on 3D unstructured grids (FY2017) and published it (FY2018), Then, through extensive investigations of various aspects of CFD schemes (e.g., turbulence models and their coefficients, numerical fluxes, slope limiters), we extended it to a zone-based Delayed DES, coined as “HR-SLAU2-DDES”. As a result, better pressure distributions on the main wing than the earlier results are successfully obtained. For instance, Figs. 1-4 show effects of the coefficient “Crot” of SA-noft2-R turbulence model. In this example, it is demonstrated that the case with Crot = 2.0 or 0.0 rather than 1.0 has suppressed an excessive separation near the leading-edge of the main wing.

Annual Reoprt Figures for 2018

Fig.1: Pressure distributions on 28.3% cross-section.

 

Annual Reoprt Figures for 2018

Fig.2: Flowfield around main wing (28.3% cross-section), Crot = 1.0 (FaSTAR default).

 

Annual Reoprt Figures for 2018

Fig.3: Flowfield around main wing (28.3% cross-section), Crot = 2.0 (NASA-recommended).

 

Annual Reoprt Figures for 2018

Fig.4: Flowfield around main wing (28.3% cross-section), Crot = 0.0 (no rotation correction).

 

Publications

– Peer-reviewed papers

Kitamura, K., Aogaki, T., Inatomi, A., Fukumoto, K., Takahama, T., and Hashimoto, A.: Post Limiters and Simple Dirty-Cell Detection for Three-Dimensional, Unstructured, (Unlimited) Aerodynamic Simulations, AIAA Journal, Vol. 56, No. 8, 2018, pp. 3192-3204. doi:10.2514/1.J056683

– Oral Presentations

Keiichi Kitamura, Suguru Ogawa, Hiroyuki Takimoto, Masashi Kanamori, and Atsushi Hashimoto, “Low Speed Buffet Simulation using High-Resolution Delayed-DES”, 51st Fluid Dynamics Conference/37th Aerospace Numerical Simulation Symposium (to be presented, Jul-2019) (in Japanese)

Usage of JSS2

Computational Information

  • Process Parallelization Methods: MPI
  • Thread Parallelization Methods: OpenMP
  • Number of Processes: 512
  • Elapsed Time per Case: 19.73 Hour(s)

Resources Used

 

Fraction of Usage in Total Resources*1(%): 1.12

 

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 8,084,309.15 0.99
SORA-PP 308,026.29 2.46
SORA-LM 26,345.55 12.28
SORA-TPP 0.00 0.00

 

File System Resources
File System Name Storage Assigned
(GiB)
Fraction of Usage*2(%)
/home 580.60 0.60
/data 44,527.07 0.79
/ltmp 19,287.12 1.65

 

Archiver Resources
Archiver Name Storage Used
(TiB)
Fraction of Usage*2(%)
J-SPACE 12.38 0.43

*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