JAXA Special Publication JAXA-SP-19-003E

Research on combustor simulation
Report Number: R18ETET05
Subject Category: Skills Acquisition SystemURL: https://www.jss.jaxa.jp/en/ar/e2018/9166/
Responsible Representative
Takashi Aoyama, Aeronautical Technology Directorate, Numerical Simulation Research Unit
Contact Information
Himeko Yamamoto (himeko@toki.waseda.jp)
Members
Himeko Yamamoto
Abstract
For the development of a aircraft engine combustor with high environmental compatibility, we develop thecombustion calculation method that can reproduce the pressure propagation and chemical reaction with practical
calculation cost. In addition, a verification calculation of this calculation method is conducted on the scramjet test
engine of DLR.
Reasons for using JSS2
It is necessary to use supercomputer to conduct development and verification of the combustion calculation
method.
Achievements of the YearThe laminar flamelet model, which is a tabulated-chemistry calculation method, is effective for reducing theinflexibility of numerical simulation of combustion. However, the recently proposed compressible flamelet model,
which is applicable to compressible flow, has some problems related to increased complication of the flamelet
table and the pressure-calculation process. To address these problems of the conventional formulation of thecompressible flamelet model (method A), we propose two formulations (methods B and C). Method B improves
the calculation speed by choosing thermochemical properties of a multicomponent gas and a part of the subgridscale term as outputs of the flamelet tables. Method C reduces the memory usage of the flamelet tables drasticallyby applying the artificial neural networks to the formulation of method B. To evaluate these methods in an actual
combustion field, we conducted numerical simulations (Fig. 2, Fig. 3) based on the German Aerospace Centerscramjet test-engine combustor (Fig. 1).

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JAXA Supercomputer System Annual Report (April 2018-March 2019)

Fig. 1: DLR Scramjet test engine combustor

Fig. 2: Axial velocity distribution(experiment, method A, method B, method C, previous study (F. Genin, 2010))

Fig. 3: Temperature distribution(experiment, method A, method B, method C, previous study (F. Genin, 2010))－309－

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JAXA Special Publication JAXA-SP-19-003EPublications- Peer-reviewed papers
Himeko Yamamoto, Rui Toyonaga, Yusuke Komatsu, Koki Kabayama, Yasuhiro Mizobuchi, Tetsuya Sato,“Improvement of Laminar Flamelet Moedl for Compressible Flows Using Artificial Neural Network”, Aerospace
Technology Japan (Online Journal, In Japanese), Japan Society for Aeronautical and Space Sciences (2018.11,accepted)- Poster Presentations
Himeko Yamamoto, Rui Toyonaga, Yusuke Komatsu, Koki Kabayama, Yasuhiro Mizobuchi, Tetsuya Sato,“Generation of Thermochemical Database Using Artificial Neural Network For Compressible Flamelet
Approach”, International Symposium on Combustion, WiPP session, Ireland, 2018.8

Usage of JSS2

Computational Information
Process Parallelization Methods

MPIThread Parallelization Methods

N/A

Number of Processes

2 - 1024

Elapsed Time per Case

120 Hour (s)Resources Used
Fraction of Usage in Total Resources*1 (%): 0.46
Details
Computational Resources
System Name

Amount of Core Time(core x hours)

Fraction of Usage*2 (%)

SORA-MA

3,869,594.74

0.47

SORA-PP

31,509.90

0.25

SORA-LM

0.00

0.00

SORA-TPP

0.00

0.00

File System Resources
File System Name

Storage Assigned (GiB)

Fraction of Usage*2 (%)/home476.84

0.49

/data

39,062.52

0.69/ltmp

1,953.13

0.17

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JAXA Supercomputer System Annual Report (April 2018-March 2019)

Archiver Resources
Archiver Name

Storage Used (TiB)

J-SPACE

Fraction of Usage*2 (%)
0.48

0.02

*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.

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