联系我们
意见反馈

关注公众号

获得最新科研资讯

刘有晟老师课题组

简介 刘有晟老师课题组

分享到

Novel modelling method for vaporization complex hydrocarbon fuels

L. Luo, Y.C. Liu, "Variation of gas phase combustion properties of complex fuels during vaporization: comparison for distillation and droplet scenarios," Proceedings of the Combustion Institute 38 (2021) 3287-3294.

Surrogate mixtures for modelling real fuels are formulated based on gaseous combustion property targets and liquid physical properties. A batch distillation model was developed to evaluate the vaporization characteristics of some existing surrogates for Jet-A. Chinese aviation fuel RP-3 was then used as a target to experimentally obtain distillation curves and variation of chemical functional groups. A 24-component surrogate was formulated mainly to capture the distillation behavior of RP-3. This surrogate was then used in two droplet vaporization models (Finite Thermal Conductivity/Finite Diffusivity (FTC/FD), Infinite Thermal Conductivity/Infinite Diffusivity (ITC/ID)) to investigate the effects of preferential vaporization on gaseous combustion properties of a complex real fuel. The results obtained from FTC/FD and ITC/ID provide regional bounds for droplets in a vaporizing spray. Four combustion property targets (Molecular Weight (MW), Hydrogen to Carbon ratio (H/C), Derived Cetane Number (DCN) and Threshold Sooting Index (TSI)) were employed as indicators of gas combustion properties. It was found that due to a wide distribution of compounds’ volatility, gaseous combustion properties vary significantly during droplet vaporization. The results suggest development of vaporization models that well capture preferential vaporization of a target real fuel for further spray modelling.

-------------------------------------------------------------------------------------------------------------

L. Luo, Y.C. Liu, "An "artificial" activity coefficient modelling approach for emulating combustion and physical property variations during distillation of real complex fuel", Combustion and Flame 230 (2021) 111446.

       Real complex fuels consist of hundreds of species and hence are difficult to model in numerical simulation. There have been many methods to formulate simple surrogate suite composed of several compounds. While these surrogates emulate gaseous combustion properties with acceptable fidelity, due to insufficient number of surrogate components comprehensive distillation behaviors of simple surrogates exhibit considerable discrepancy compared to that of real complex fuels. In this work, we demonstrated a new methodology for representing complex fuel economically. Firstly, we obtained information about functional group evolution of a complex fuel (Chinese aviation fuel, RP-3) from distillation experiments and formulated a rather complex surrogate mixture. Then, a Functional Group Matching (FGM) method was applied to convert the complex surrogate to a target 4-component surrogate mixture with an “artificial” activity coefficient model (AACM) such that distillation of real complex fuels can be accurately replicated. This “artificial” activity coefficient model was validated in batch distillation simulation in comparison with the complex surrogate with conventional phase equilibrium model (UNIQUAC Functional-group Activity Coefficient (UNIFAC)). Results showed that chemical functional groups, combustion property targets (CPTs) and physical properties (density, surface tension, and dynamic viscosity) during a distillation process of the simple surrogate well represented those of the complex surrogate. Also, the computational efficiency of this 4-component surrogate with AACM method was verified, which was thousands of times faster than 24-component mixture with UNIFAC. The “artificial” activity coefficient model for a simple surrogate mixture therefore contained the most authentic physics from the distillation experiments of a real complex fuel with potential to improve the computational efficiency and to couple with the chemical kinetics mechanisms available to the simple surrogate.

创建: Dec 28, 2021 | 17:44