title: Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine.
abstract: In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operating parameters on combustion rate was also studied by means of this model. The study showed that the predicted results were good agreement with the experimental data. It was proved that the developed combustion rate model could be used to successfully predict and optimize the combustion process of dual fuel engine.
authors.affiliation: Department of Energy Engineering, Zhejiang University, Hangzhou 310027, China.
authors.forename: Zhao-Da
authors.initials: ZD
authors.lastname: Yan
authors.forename: Chong-Guang
authors.initials: CG
authors.lastname: Zhou
authors.forename: Shi-Chuan
authors.initials: SC
authors.lastname: Su
authors.forename: Zhen-Tao
authors.initials: ZT
authors.lastname: Liu
authors.forename: Xi-Zhen
authors.initials: XZ
authors.lastname: Wang
mesh_terms: D000393:Air Pollutants; D000397:Air Pollution / Q000517:prevention & control; D003198:Computer Simulation; D011211:Electric Power Supplies; D004735:Energy Transfer; D004736:Energy-Generating Resources; D005579:Fossil Fuels; D005742:Gasoline; D006358:Hot Temperature; D008956:Models, Chemical; D008962:Models, Theoretical; D018986:Motor Vehicles; D016571:Neural Networks, Computer; D010084:Oxidation-Reduction; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013816:Thermodynamics; D001335:Vehicle Emissions / Q000032:analysis
chemical_list: D000393:Air Pollutants; D005579:Fossil Fuels; D005742:Gasoline; D001335:Vehicle Emissions