Description of the char conversion process in coal combustion based on premixed FGM chemistry. (15th January 2019) - Knappstein, R.; Kuenne, G.; Nicolai, H.; di Mare, F.; Sadiki, A.; Janicka, J.
Abstract: This work presents and assesses a tabulation approach to represent the complex coal combustion chemistry at low computational costs. It should enable to include the process of volatiles conversion and char burnout in scale resolving simulations (such as large eddy simulations) of realistic coal combustion chambers. It is based on premixed flamelets and gets investigated with respect to its capability to accurately describe char conversion. In this approach the gas phase chemistry is mapped onto a four-dimensional manifold controlled by two mixture fractions, the enthalpy and a reaction progress variable. Accordingly, mixing between oxidizer, volatiles and gaseous char conversion products is accounted for besides non-adiabatic physics and finite rate chemistry effects. In a previous work (Knappstein et al., 2017), several modeling assumptions with regard to the description of the volatiles reaction using tabulated chemistry were already assessed. For the full description of the coal combustion process the model functionality was extended to account also for char conversion in the present work. Here, special emphasis is therefore put on aspects related with the conversion of char. The consistency of the model formulation and its implementation is demonstrated by the examination of mass, species and energy balances in generic test cases for which analytical solutions are derivable. Furthermore, results of a simulation adopting the presented model are compared against a detailed chemistry reference solution accounting for the full reaction mechanism. This situation approximates a particle essentially consisting of char that is exposed to hot oxygen-containing product gases. Thereby, capabilities of the presented modeling approach with respect to prediction accuracies for the model's intended application in LES can be estimated.