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

Aeroacoustic simulation of launch vehicle at lift-off
Report Number: R18EG3213
Subject Category: Research and Development
URL: https://www.jss.jaxa.jp/en/ar/e2018/9144/
Responsible Representative
Eiji Shima, Unit leader, Research Unit III, Research and Development Directorate
Contact Information
tsutsumi.seiji@jaxa.jp (tsutsumi.seiji@jaxa.jp)
Members
Ryoji Takaki, Seiji Tsutsumi, Hiroyuki Ito, Taro Shimizu, Junya Aono, Takanori Haga, Yuhi Morii, Masaharu
Abe, Masayuki Kakehi, Mikiroh Motoe, Manabu Hisida, Shun Ito, Kazuma Tago, Hiroshi Koizumi
Abstract
It is required to predict and reduce the acoustic level of satellites caused by exhaust jet of rocket engines andtransonic buffet. In this study, the lift-off acousitc analysis tool developed so far is coupled with the FEM tool topredict the acoustic level inside payload fairing, aiming to develop quiet launch vehicle.
Reasons for using JSS2
It is necessary to carry out billions of LES analysis, and large computing resources are essential to achieve thetarget frequency resolution.
Achievements of the Year
(1) Aero-vibro acoustic simulation for the prediction of harmful acoustic loading at lift-off of launch vehicle isdeveloped. In this simulation technique, high-fidelity large-eddy simulation with computational aeroacoutics
based on full-Euler equations is employed for computing jet aeroacoustics and their propagation to the outside ofpayload fairing. Acoustic field inside the payload fairing is computed by the coupled vibro-acoustic simulation
based on finite element method. A simplified fairing model is used for the validation of the present method. Animpact hammer test is conducted for validating the structural model. Then, accuracy of this method is validated
by using the acoustic vibration test result with a subscale rocket engine.
(2) Aeroacoustic simulation based on hybrid LES/RANS is conducted to predict acoustic level around a SSTO
at lift-off. (Fig. 2) It is found that the acoustic level is higher that the conventional expendatble launch vehicle
with launch pad.

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This document is provided by JAXA.

JAXA Special Publication JAXA-SP-19-003E

Fig. 1: Comparison of transfer function between experimental and numerical modal analysis

Fig. 2: Acoustic propagation of SSTO at lift-off

Publications
N/A
Usage of JSS2

Computational Information
Process Parallelization Methods

MPIThread Parallelization Methods

OpenMP

Number of Processes

512

Elapsed Time per Case

800 Hour (s)－240－This document is provided by JAXA.

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

Resources Used
Fraction of Usage in Total Resources*1 (%): 0.81
Details
Computational Resources
System Name

Amount of Core Time(core x hours)

Fraction of Usage*2 (%)

SORA-MA

6,736,350.24

0.82

SORA-PP

76,080.65

0.61

SORA-LM

1,576.29

0.73

SORA-TPP

0.00

0.00

File System Resources
File System Name

Storage Assigned (GiB)

Fraction of Usage*2 (%)/home

5,139.61

5.32/data

36,070.13

0.64/ltmp

5,848.72

0.50

Archiver Resources
Archiver Name

Storage Used (TiB)

J-SPACE

Fraction of Usage*2 (%)
117.294.10*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.

－241－This document is provided by JAXA.