Journal
- Journal of the Combustion Society of Japan Vol. 63 No. 203
CONTENTS - A Review on Applications of Machine Learning Method to Combustion Science and an Investigation of Combustion Instability Dynamics
Nakaya, S. and Tsue, M. - Reduced Dimension Analysis on Combustion Dynamics Using Deep Auto-Encoder
Tanabe, M. - Early Detection and Prevention of Combustion Oscillations in a Swirl-Stabilized Combustor -Introduction of Combined Methodologies of Symbolic Dynamics, Complex Networks, and Machine Learning-
Masuda S., Asami K., Hachijo T., Gotoda H. - Introduction to Turbulent Combustion Modelling Based on Machine Learning
Minamoto, Y. and Tanahashi, M. - Application of Neural Networks to Laminar Flamelet Model
Yamamoto, H., Mizobuchi, Y. and Sato, T. - Prediction of Pulsating Turbulent Pipe Flow Using Machine Learning
Shimura, T., Mitsuishi, A. and Iwamoto, K. - A Study on Thermal Radiation Control by Machine Learning
Sakurai, A. - Non-intrusive Particle Size Measurement Method Based on Scattered Light Intensities of Polarized Lights
Araki, M. - Optical Diagnostics for Soot Formation Characteristics in Multi-phase Combustion Field Formed in a Simplified Flow Field
Hayashi, J., Hashimoto, N. and Akamatsu, F.
The original papers and society activity notes are available at J-STAGE web site.
https://www.jstage.jst.go.jp/browse/jcombsj
[FEATURE]
- Applications of Machine Learning Method to Combustion Science -
[SERIAL LECTURE]
- Fundamentals and Applications of Combustion Measurement Technique IX -
[REVIEW PAPER]