Research and Development of Hydrogen Fueled Future Space Transportation Systems
JAXA Supercomputer System Annual Report February 2023-January 2024
Report Number: R23EDG10105
Subject Category: Research and Development
- Responsible Representative: Kouichi Okita, Director, Research and Development Directorate, Research Unit IV
- Contact Information: Masatoshi Kodera(kodera.masatoshi@jaxa.jp)
- Members: Masaaki Fukui, Chihiro Fujio, Taku Inoue, Masatoshi Kodera, Tomoaki Nara, Hideaki Ogawa, Miyu Shimmoto, Masaharu Takahashi
Abstract
High speed point to point (P2P) space transportation system seems to be promising in the community of future private space businesses. In this project, we aim at completing hydrogen fueled hypersonic engine technology, especially, control techniques changing two cycles between turbojet and scramjet engines for the combined cycle engines and transferring the technology to the private business players. As a result, we will contribute to realize the above mentioned space transportation system.
Reference URL
N/A
Reasons and benefits of using JAXA Supercomputer System
When hydrogen fueled hypersonic engines are used for space transportation systems, It is necessary to confirm the engine working characteristics in the wide range of flight speeds while a vehicle with the engine is accelerating and ascending. However, it is impossible to simulate all the flight conditions by ground experiment facilities so that the use of CFD is indispensable to compensate for the experiment. In addition, considering the change of engine cycles for the turbine based combined cycle engine, it is necessary to investigate not only each the engine performance, but also the entire engine system. For this purpose, the application of advanced optimization algorithms using CFD database is effective. Therefore, it is indispensable to utilize JSS since numerous computational resources are required to handle those subjects efficiently.
Achievements of the Year
(1) Using JSS3, we conducted 100 cases of numerical calculations for a scramjet combustor using the commercial CFD solver CFD++. Using these calculation results, a machine learning model was created to predict combustor performance (combustion efficiency, thrust, pressure ratio, etc.) from design variables, and model-based multi-objective design optimization was performed. (Fig. 1)
(2) We are conducting research on the optimization of fuel injectors for scramjet engines. For this purpose, CFD database for a wall mounted injector including 1000 cases was generated by changing randomly the injector hole shape, injection pressure and injection angle. (Fig. 2) In addition, CFD database for a hypermixer injector including 430 cases was also generated by changing the ramp angle, injector hole interval and fuel equivalence ratio.

Fig.2: Example of CFD database for wall mounted fuel injector (left: injector hole shape, middle: Mach contours on symmetry plane, right: H2 distributions on combustor exit)
Publications
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Usage of JSS
Computational Information
- Process Parallelization Methods: MPI
- Thread Parallelization Methods: OpenMP
- Number of Processes: 256 – 512
- Elapsed Time per Case: 12 Hour(s)
JSS3 Resources Used
Fraction of Usage in Total Resources*1(%): 0.01
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 | 89644.31 | 0.00 |
TOKI-ST | 345.78 | 0.00 |
TOKI-GP | 0.00 | 0.00 |
TOKI-XM | 0.00 | 0.00 |
TOKI-LM | 54.01 | 0.00 |
TOKI-TST | 0.00 | 0.00 |
TOKI-TGP | 0.00 | 0.00 |
TOKI-TLM | 0.00 | 0.00 |
File System Name | Storage Assigned(GiB) | Fraction of Usage*2(%) |
---|---|---|
/home | 112.02 | 0.09 |
/data and /data2 | 2061.43 | 0.01 |
/ssd | 0.00 | 0.00 |
Archiver Name | Storage Used(TiB) | Fraction of Usage*2(%) |
---|---|---|
J-SPACE | 4.13 | 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.
ISV Software Licenses Used
ISV Software Licenses Used(Hours) | Fraction of Usage*2(%) | |
---|---|---|
ISV Software Licenses(Total) | 432.31 | 0.20 |
*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.
JAXA Supercomputer System Annual Report February 2023-January 2024