A detailed chemical mechanism to describe the combustion of natural gas in internal combustion （IC） engine has been developed,which is consisting of 233 reversible reactions and 79 species.This mechanism accounts fo...A detailed chemical mechanism to describe the combustion of natural gas in internal combustion （IC） engine has been developed,which is consisting of 233 reversible reactions and 79 species.This mechanism accounts for the oxidation of methane,ethane,propane and nitrogen.It has been tested using IC engine model of CHEMKIN 4.1.1 and experimental measurements.The performance of the proposed mechanism was evaluated at various equivalence ratios （φ=0.6 to φ=1.3）,initial reactor conditions （Tini=500 to 3500 ℃; Pini=1.0 to 10 atm） and engine speed （2000-7000 rpm）.The proposed kinetic mechanism shows good concordances with GRI3.0 mechanism especially in the prediction of temperature,pressure and major product species （H2O,CO2） profiles at stoichiometric conditions （φ=1.0）.The experimental results of measured cylinder pressure,species fractions were also in agreement with simulation results derived from the proposed kinetic mechanism.The proposed mechanism successfully predicts the formation of gaseous pollutants （CO,NO,NO2,NH3） in the engine exhaust.Although there are some discrepancies among each simulation profile,the proposed detailed mechanism is good to represent the combustion of natural gas in IC engine.展开更多
The partial oxidation of hydrocarbons is an important technical route to produce acetylene for chemical industry.The partial oxidation reactor is the key to high acetylene yields.This work is an experimental and numer...The partial oxidation of hydrocarbons is an important technical route to produce acetylene for chemical industry.The partial oxidation reactor is the key to high acetylene yields.This work is an experimental and numerical study on the use of a methane flame to produce acetylene.A lab scale partial oxidation reactor was used to produce ultra fuel-rich premixed jet flames.The axial temperature and species concentration profiles were measured for different equivalence ratios and preheating temperatures,and these were compared to numerical results from Computational Fluid Dynamics(CFD)simulations that used the Reynolds Averaged Navier-Stokes Probability Density Function(RANS-PDF)approach coupled with detailed chemical mechanisms.The Leeds 1.5,GRI 3.0 and San Diego mechanisms were used to investigate the effect of the detailed chemical mechanisms.The effects of equivalence ratio and preheating temperature on acetylene production were experimentally and numerically studied.The experimental validations indicated that the present numerical simulation provided reliable prediction on the partial oxidation of methane.Using this simulation method the optimal equivalence ratio for acetylene production was determined to be 3.6.Increasing preheating temperature improved acetylene production and shortened greatly the ignition delay time.So the increase of preheating temperature had to be limited to avoid uncontrolled ignition in the mixing chamber and the pyrolysis of methane in the preheater.展开更多
This paper systematically develops a high-fidelity turbulent combustion surrogate model using deep learning.We construct a surrogate model to simulate the turbulent combustion process in real time,based on a state-oft...This paper systematically develops a high-fidelity turbulent combustion surrogate model using deep learning.We construct a surrogate model to simulate the turbulent combustion process in real time,based on a state-ofthe-art spatiotemporal forecasting neural network.To address the issue of shifted distribution in autoregressive long-term prediction,two training techniques are proposed:unrolled training and injecting noise training.These techniques significantly improve the stability and robustness of the model.Two datasets of turbulent combustion in a combustor with cavity and a vitiated co-flow burner(Cabra burner)have been generated for model validation.The effects of model architecture,unrolled time,noise amplitude,and training dataset size on the long-term predictive performance are explored.The well-trained model can be applicable to new cases by extrapolation and give spatially and temporally consistent results in long-term predictions for turbulent reacting flows that are highly unsteady.展开更多
文摘A detailed chemical mechanism to describe the combustion of natural gas in internal combustion （IC） engine has been developed,which is consisting of 233 reversible reactions and 79 species.This mechanism accounts for the oxidation of methane,ethane,propane and nitrogen.It has been tested using IC engine model of CHEMKIN 4.1.1 and experimental measurements.The performance of the proposed mechanism was evaluated at various equivalence ratios （φ=0.6 to φ=1.3）,initial reactor conditions （Tini=500 to 3500 ℃; Pini=1.0 to 10 atm） and engine speed （2000-7000 rpm）.The proposed kinetic mechanism shows good concordances with GRI3.0 mechanism especially in the prediction of temperature,pressure and major product species （H2O,CO2） profiles at stoichiometric conditions （φ=1.0）.The experimental results of measured cylinder pressure,species fractions were also in agreement with simulation results derived from the proposed kinetic mechanism.The proposed mechanism successfully predicts the formation of gaseous pollutants （CO,NO,NO2,NH3） in the engine exhaust.Although there are some discrepancies among each simulation profile,the proposed detailed mechanism is good to represent the combustion of natural gas in IC engine.
基金Supported by the National Natural Science Foundation of China(20976090)the Foundation for the Author of National Excellent Doctoral Dissertation of China(200757)
文摘The partial oxidation of hydrocarbons is an important technical route to produce acetylene for chemical industry.The partial oxidation reactor is the key to high acetylene yields.This work is an experimental and numerical study on the use of a methane flame to produce acetylene.A lab scale partial oxidation reactor was used to produce ultra fuel-rich premixed jet flames.The axial temperature and species concentration profiles were measured for different equivalence ratios and preheating temperatures,and these were compared to numerical results from Computational Fluid Dynamics(CFD)simulations that used the Reynolds Averaged Navier-Stokes Probability Density Function(RANS-PDF)approach coupled with detailed chemical mechanisms.The Leeds 1.5,GRI 3.0 and San Diego mechanisms were used to investigate the effect of the detailed chemical mechanisms.The effects of equivalence ratio and preheating temperature on acetylene production were experimentally and numerically studied.The experimental validations indicated that the present numerical simulation provided reliable prediction on the partial oxidation of methane.Using this simulation method the optimal equivalence ratio for acetylene production was determined to be 3.6.Increasing preheating temperature improved acetylene production and shortened greatly the ignition delay time.So the increase of preheating temperature had to be limited to avoid uncontrolled ignition in the mixing chamber and the pyrolysis of methane in the preheater.
基金support from the National Natural Science Foundation of China(Grant No.52250710681 and 52022091)Support from the UK Engineering and Physical Sciences Research Council under the project“UK Consortium on Mesoscale Engineering Sciences(UKCOMES)”(Grant No.EP/X035875/1)is also acknowledged.
文摘This paper systematically develops a high-fidelity turbulent combustion surrogate model using deep learning.We construct a surrogate model to simulate the turbulent combustion process in real time,based on a state-ofthe-art spatiotemporal forecasting neural network.To address the issue of shifted distribution in autoregressive long-term prediction,two training techniques are proposed:unrolled training and injecting noise training.These techniques significantly improve the stability and robustness of the model.Two datasets of turbulent combustion in a combustor with cavity and a vitiated co-flow burner(Cabra burner)have been generated for model validation.The effects of model architecture,unrolled time,noise amplitude,and training dataset size on the long-term predictive performance are explored.The well-trained model can be applicable to new cases by extrapolation and give spatially and temporally consistent results in long-term predictions for turbulent reacting flows that are highly unsteady.
