A machine learning approach assisting soot radiation-based thermometry to recover complete flame temperature field in a laminar flame
- 19 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Applied Physics B Laser and Optics
- Vol. 127 (3), 1-8
- https://doi.org/10.1007/s00340-021-07591-z
Abstract
No abstract availableKeywords
Funding Information
- NSFC (51706140)
- Natural Science Foundation of Shanghai (20ZR1426900)
This publication has 26 references indexed in Scilit:
- Soot predictions in premixed and non-premixed laminar flames using a sectional approach for PAHs and sootCombustion and Flame, 2012
- Soot pyrometry using modulated absorption/emissionCombustion and Flame, 2001
- Experimental study of nonfuel hydrocarbons and soot in coflowing partially premixed ethylene/air flamesCombustion and Flame, 2000
- Computational and experimental study of soot formation in a coflow, laminar ethylene diffusion flameSymposium (International) on Combustion, 1998
- Temperature measurements in flames using thermally assisted laser-induced fluorescence of GaApplied Optics, 1991
- Temperature / soot volume fraction correlations in the fuel-rich region of buoyant turbulent diffusion flamesCombustion and Flame, 1990
- The Transport and Growth of Soot Particles in Laminar Diffusion FlamesCombustion Science and Technology, 1987
- Soot particle measurements in diffusion flamesCombustion and Flame, 1983
- CARS thermometry in a sooting flameCombustion and Flame, 1979