Investigation of radiation models in entrained-flow coal gasification simulation

Adequate modeling of radiation heat transfer is important in CFD simulation of coal gasification process. In an entrained-flow gasifer, the non-participating effect of coal particles, soot, ashes, and reactive gases could significantly affect the temperature distribution in the gasifier and hence affects the local reaction rate and life expectancy of wall materials. For slagging type gasifiers, radiation further affects the forming process of corrosive slag on the wall which can expedite degradation of the refractory lining in the gasifier. For these reasons, this paper focuses on investigating applications of five different radiation models to coal gasification process, including Discrete Transfer Radiation Model (DTRM), P-1 Radiation Model, Rosseland Radiation Model, Surface-to-Surface (S2S) Radiation Model, and Discrete Ordinates (DO) Radiation Model. The objective is to identify the pros and cons of each model’s applicability to the gasification process and determine which radiation model is most appropriate for simulating the process in entrained-flow gasifiers.The Eulerian–Lagrangian approach is applied to solve the Navier–Stokes equations, nine species transport equations, and seven global reactions consisting of three heterogeneous reactions and four homogeneous reactions. The coal particles are tracked with the Lagrangian method. Six cases are studied—one without the radiation model and the other five with different radiation models. The result reveals that the various radiation models yield uncomfortably large uncertainties in predicting syngas composition, syngas temperature, and wall temperature. The Rosseland model does not yield reasonable and realistic results for gasification process. The DTRM model predicts very high syngas and wall temperatures in the dry coal feed case. In the one-stage coal slurry case, DTRM result is close to the S2S result. The P1 method seems to behave stably and is robust in predicting the syngas temperature and composition; it yields the result most close to the mean, but it seems to underpredict the gasifier’s inner wall temperature.