Prediction of Flame Type and Liftoff Height of Fuel Jets in Turbulent Hot Coflow Using Machine Learning Methods-Reference-Cited by-同舟云学术

Prediction of Flame Type and Liftoff Height of Fuel Jets in Turbulent Hot Coflow Using Machine Learning Methods

Published:2024-01-08 Issue: Volume: Page:1-23
ISSN:0010-2202
Container-title:Combustion Science and Technology
language:en
Short-container-title:Combustion Science and Technology

Author:

Liu Jiayue¹,Liu Guijun¹^ORCID,Wu Jiahao¹,Zhang Guihua¹,Wu Yuxin¹

Affiliation:

1. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Low Carbon Energy and CCUS Research Center, Institute for Carbon Neutrality, Department of Energy and Power Engineering, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

National Science and Technology Major Project

Publisher

Informa UK Limited

Subject

General Physics and Astronomy,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00102202.2023.2295323

Reference59 articles.

1. LES of Delft Jet-in-Hot Coflow burner to investigate the effect of preferential diffusion on autoignition of CH4/H2 flames

2. Toward Decarbonized Power Generation With Gas Turbines by Using Sequential Combustion for Burning Hydrogen

3. Machine Learning for Fluid Mechanics

4. Perspective of the role of hydrogen in the 21st century energy transition

5. Chang, Y., L. Zhang, X. Wang, S. Yeh, S. Mak, C. Sung, and V. Yang. 2017. Spatial-temporal flow dynamics prediction with large design space via data-driven analysis and LES-based surrogate model. Paper presented at the ILASS-Americas 29th Annual Conference on liquid atomization and spray systems, Atlanta, GA, May 15.