Development of a combustion reaction model for lubricant synthetic base oil by experimental and numerical methods
Combustion and Flame(2022)
摘要
The synthetic base oil (SyBO) is the main component of lubricant oil, determining its basic physical and chemical properties, as well as impacting the pre-ignition, in-cylinder combustion and emission characteristics during the engine applications. Yet the involvement of SyBO in the engine combustion process is rarely investigated, primarily due to the lack of a proper combustion reaction model. The objective of the present study was to develop a fundamentally based combustion reaction model for SyBO, through the joint experimental and theoretical methods. A comprehensive set of experimental techniques was used to characterize the physicochemical properties of SyBO. Results showed that SyBO consisted of 13 large hydrocarbon molecules, ranging from C21 to C54, with mostly linear or lightly branched alkanes. A kinetic modeling approach was developed to systematically construct the reaction model for each component, which were then combined to create the full-component reaction model of SyBO. The accuracy of the thus-developed combustion reaction model was verified by a theoretically calculated ignition delay (ID) data and experimental measurements. The full-component model of SyBO was then reduced by the directed relation graph with error propagation (DRGEP) method to contain 87 species and 647 reactions. To further reduce the size of kinetic model as well as predict the physiochemical properties of SyBO, one surrogate molecule, i-C39H80, through the quantitative structure-property relationship (QSPR) of functional groups in SyBO, as well as one surrogate component, n-C54H110, were proposed. Again, the reaction model for the surrogate molecule was developed, verified, and then reduced to contain 73 species and 530 reactions, which might be applicable to computational fluid dynamics (CFD) simulations for practical engine systems.
更多查看译文
关键词
Lubricant oil,Synthetic base oil,Combustion reaction model,Surrogate fuel molecule,Chemical functional groups
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要