Machine learning model to predict the laminar burning velocities of H2/CO/CH4/CO2/N2/air mixtures at high pressure and temperature conditions

被引:28
作者
Varghese, Robin John [1 ]
Kumar, Sudarshan [1 ]
机构
[1] Indian Inst Technol, Mumbai 400076, Maharashtra, India
关键词
Laminar burning velocity; Machine learning; Temperature exponent; Pressure exponent; Syngas; AIR PREMIXED FLAMES; ELEVATED-TEMPERATURES; H-2-CO MIXTURES; CO2; DILUTION; SPEEDS; STABILITY; HYDROGEN; FUEL; COMBUSTION; H-2/CO;
D O I
10.1016/j.ijhydene.2019.11.134
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
An empirical model based on machine learning is developed for predicting the variation of the laminar burning velocities of H-2/CO/CH4/CO2/N-2/air mixtures with volumetric fractions as the independent variables at different elevated mixture temperatures and pressures. The proposed model is derived partly based on the measured burning velocities of syngas-air mixtures at elevated temperatures and pressures using diverging channel method, and partly established from the predictions using the FFCM-1 detailed kinetic model. The experiments at elevated pressures and temperature strongly agree with the predictions of the FFCM-1 kinetic model for PG1 (H-2/CO/CO2/N-2 = 15/15/15/55) syngas composition. Based on the detailed analysis of the experimental results, a power-law correlation considering the alpha, beta variations is proposed: S-u = S-u,S-o *(T-u/T-u,T-o)(alpha 0+alpha 1(1-Pu/Pu,o)) * (P-u/P-u,P-o)(beta 0+beta 1 (1-Tu/Tu,o)). Machine learning model (multiple linear-regression) was trained for the variables (S-u,S-o, alpha(0), alpha(1), beta(0), beta(1)) in the power-law correlation to enable the prediction of laminar burning velocity at various pressure and temperature conditions. The empirical model was developed with mole fractions of various components (H-2/CO/CH4/CO2/N-2) in the syngas composition and equivalence ratio as independent variables. The developed model was intended for low-calorific value syngas mixtures, and it performs exceedingly well without solving detailed governing equations, detailed chemistry, and transport equations. The proposed model is accurate for a wide range of syngas-air mixtures reported in the literature. A detailed comparison showed that the empirical model accurately predicts the laminar burning velocity with error <10%, for a wide range of H-2/CO/CH4/CO2/N-2/Air mixtures with 0.25 < X-H2 < 0.70, 0.25 < X-CO < 0.70, 0 < X-CH4 < 0.15, 0 < X-CO2 < 0.50, 0 < X-N2 < 0.70, for equivalence ratios of phi = 0.5-2.5, mixture temperatures from 300 to 650 K, and pressures from 1 to 5 atm. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:3216 / 3232
页数:17
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