Early Detection of Thermoacoustic Combustion Instability Using a Methodology Combining Complex Networks and Machine Learning-Reference-Cited by-同舟云学术

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Early Detection of Thermoacoustic Combustion Instability Using a Methodology Combining Complex Networks and Machine Learning

Published:2019-06-14 Issue:6 Volume:11 Page:
ISSN:2331-7019
Container-title:Physical Review Applied
language:en
Short-container-title:Phys. Rev. Applied

Author:

Kobayashi Tsubasa,Murayama Shogo,Hachijo Takayoshi,Gotoda Hiroshi

Funder

Grant-in-Aid for Scientific Research

Suzuki Foundation

Tokyo University of Science

Publisher

American Physical Society (APS)

Subject

General Physics and Astronomy

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevApplied.11.064034/fulltext

Reference32 articles.

1. Measurements of acoustic streaming in a looped-tube thermoacoustic engine with a jet pump

2. Low temperature differential thermoacoustic Stirling engine

3. Dynamics and stability of lean-premixed swirl-stabilized combustion

4. Unsteady Combustor Physics

5. Sensitivity and Nonlinearity of Thermoacoustic Oscillations

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