• 한국연소학회:학술대회논문집
• /
• 2012.04a
• /
• pp.37-40
• /
• 2012

In an entrained flow coal gasifier, predicting the reaction behavior of pulverized coal particles requires detailed information on devolatilization, char gasification, gaseous reactions, turbulence and heat transfer. Among the input parameters, the rate of devolatilization and the composition of volatile species are difficult to determine by experiments due to a high pressure (~40 bar) and temperature (${\sim}1500^{\circ}C$). This study investigates the effect of devolatilization models on the reaction and heat transfer characteristics of a 300 MWe Shell coal gasifier. A simplified devolatilization model and advanced model based on Flashchain were evaluated, which had different volatiles composition and devolatilization rates. It was found that the tested models produce similar flow and reaction trends, but the simplified model slightly over-predict the temperature and wall heat flux near the coal inlets.

• 한국연소학회:학술대회논문집
• /
• 2012.04a
• /
• pp.217-219
• /
• 2012

This study describes 3D RANS simulation of a 2.1 MW swirling pulverized coal flame in a semi-industrial scale furnace. The simulation of pulverized coal combustion involves various models for complex physical processes and needs information of pyrolysis rate, the yields and compositions of volatiles and char especially in coal conversion. The coal conversion information can be acquired by the experiment or the pre-processor code. The empirical model based on the experiment of the IFRF and the structural model based on the pre-processor code of the PC-COAL-LAB were evaluated against the measurement data.

• 한국연소학회:학술대회논문집
• /
• 2014.11a
• /
• pp.59-62
• /
• 2014

Predicting coal combustion by computational fluid dynamics (CFD) requires a combination of complicated flow and reaction models for turbulence, radiation, particle flows, heterogeneous combustion, and gaseous reactions. There are various levels of models available for each of the phenomena, but the use of advanced models are significantly restricted in a large-scale boiler due to the computational costs and the balance of accuracy between adopted models. In this study, the influence of coal devolatilization model and turbulent mixing rate was assessed in CFD for a commercial boiler at 500 MWe capacity. For coal devolatilization, two models were compared: i) a simple model assuming single volatile compound based on proximate analysis and ii) advanced model of FLASHCHAIN with multiple volatile species. It was found out that the influence of the model was observed near the flames but the overall gas temperature and heat transfer rate to the boiler were very similar. The devolatilization rate was found not significant since the difference in near-flame temperature became noticeable when it was multiplied by 10 or 0.1. In contrast, the influence of turbulent mixing rate (constant A in the Magnussen model) was found very large. Considering the heat transfer rate and flame temperature, a value of 1.0 was recommended for the rate constant.