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61958040.pdf1.42 MB
titleデータマイニングによる斜め平板に衝突する超音速ジェットから発生する音響波の理解
Other TitleData Mining for the Understanding of Acoustics Waves Generation from a Supersonic Jet Impinging on Inclined Flat Plate
Author(jpn)森澤, 征一郎; 野々村, 拓; 大山, 聖; 藤井, 孝藏; 大林, 茂
Author(eng)Morizawa, Seiichiro; Nonomura, Taku; Oyama, Akira; Fujii, Kozo; Obayashi, Shigeru
Author Affiliation(jpn)東北大学大学院; 宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS); 宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS); 宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS); 東北大学流体科学研究所
Author Affiliation(eng)Tohoku University; Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS); Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS); Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA)(ISAS); Institute of Fluid Science, Tohoku University
Issue Date2013-03-29
Publisher宇宙航空研究開発機構(JAXA)
Japan Aerospace Exploration Agency (JAXA)
Publication title宇宙航空研究開発機構特別資料
JAXA Special Publication: Proceedings of 44th Fluid Dynamics Conference / Aerospace Numerical Simulation Symposium 2012
VolumeJAXA-SP-12-010
Start page237
End page242
Publication date2013-03-29
Languagejpn
eng
AbstractKey features from acoustics waves generated from a supersonic jet impinging on three kinds of inclined flat plates are extracted by applying two types of data mining techniques. One is cluster analysis which consists of self-organizing map and k-means method, and the other is proper orthogonal decomposition (POD) with Fourier transformation. The flow data is taken from the numerical simulation data in the previous study. First, the cluster analysis is applied to the dataset based on the normalization of the sound pressure level spectra on symmetrical plane. The results show the apparent characterization of regions based the frequencies of acoustics waves. Clusters corresponding to three kinds of acoustics waves are clearly generated. Next, POD is applied to two-dimensional pressure distribution in the acoustics fields. The results reveal the source locations where strong acoustics waves are generated. These results agree with the previous obse""" rvations. Thus, this study shows the capability of data mining to extract key features of acoustics waves generated from the flow field.
Description会議情報: 第44回流体力学講演会/航空宇宙数値シミュレーション技術シンポジウム2012 (2012年7月5日-6日. 富山国際会議場大手町フォーラム), 富山市, 富山県
形態: カラー図版あり
Meeting Information: 44th Fluid Dynamics Conference / Aerospace Numerical Simulation Symposium 2012 (July 5-6, 2012. Toyama International Conference Center), Toyama Japan
Physical characteristics: Original contains color illustrations
Document TypeConference Paper
JAXA Category特別資料
ISSN1349-113X
NCIDAA11984031
SHI-NOAA0061958040
Report NoJAXA-SP-12-010
URIhttps://repository.exst.jaxa.jp/dspace/handle/a-is/14726


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