An efficient multi-component fuel droplet vaporization model has been developed in this work using discrete approach. The precise modeling of droplet vaporization process is divided into two parts: vapor-phase and liquid-phase sub-models. Temporal evolution of flow inside the droplet is considered to describe the transient behavior introduced by the slow diffusion process. In order to account for the internal circulation motion, surface regression and finite diffusion without actually resolving the spatial governing equations within the liquid phase, a set of ordinary differential equations is applied to describe the evolution of the non-uniform distributions of universal diffusional variables, i.e. temperature and species mass fraction. The differences between the droplet surface and bulk mean states are modeled by constructing a quasi-1D frame; the effect of the internal circulations is taken into consideration by using the effective diffusivity rather than physical diffusivity. Peng-Robinson (PR) Equation of State (EOS) is utilized to deliberate the non-ideal behavior in a high-pressure environment and to compute the vapor-liquid equilibrium (VLE) at droplet surface. The quasi-steady assumption is made for the gaseous flow in determining vaporization rate and heat flux to the droplet. Model results are compared with the measured data from fuel droplet evaporation experiments using suspending silica filament technique in a constant volume chamber (CVC). The support filament has a 100-μm diameter to minimize the effect of thermal conduction. The experiments are carried out with different ambient temperatures. Droplet lifetime and vaporization rate are determined from the data recorded by a high-speed CCD camera. Droplet temperature is acquired by a thermocouple with 50 μm diameter. The comparison demonstrates the capability of the model in predicating the droplet size and temperature change under the low pressure condition at various ambient temperatures. Under the high pressure conditions, though the proposed model predicted a slow initial heat-up process which in turns lengthens the droplet lifetime, the prediction of vaporization rate necessarily agrees with the measured data.
ASJC Scopus subject areas
- Automotive Engineering
- Safety, Risk, Reliability and Quality
- Industrial and Manufacturing Engineering