The paper presents the results of numerical computations performed for the furnace chamber waterwalls of a supercritical boiler with a steam output of 2400 × 103 kg/h. A model of distributed parameters is proposed for the waterwall operation simulation. It is based on the solution of equations describing the mass, momentum and energy conservation laws. The aim of the calculations was to determine the distribution of enthalpy, mass flow and fluid pressure in tubes. The balance equations can be brought to a form where on the left-hand side space derivatives, and on the right-hand side – time derivatives are obtained. The time derivatives on the right-hand side were replaced with backward difference quotients. This system of ordinary differential equations was solved using the Runge-Kutta method. The calculation also takes account of the variable thermal load of the chamber along its height. This thermal load distribution is known from the calculations of the heat exchange in the combustion chamber. The calculations were carried out with the zone method.

The interrelation between fuzzy logic and cluster renewal approaches for heat transfer modeling in a circulating fluidized bed (CFB) has been established based on a local furnace data. The furnace data have been measured in a 1296 t/h CFB boiler with low level of flue gas recirculation. In the present study, the bed temperature and suspension density were treated as experimental variables along the furnace height. The measured bed temperature and suspension density were varied in the range of 1131–1156 K and 1.93–6.32 kg/m3, respectively. Using the heat transfer coefficient for commercial CFB combustor, two empirical heat transfer correlation were developed in terms of important operating parameters including bed temperature and also suspension density. The fuzzy logic results were found to be in good agreement with the corresponding experimental heat transfer data obtained based on cluster renewal approach. The predicted bed-to-wall heat transfer coefficient covered a range of 109–241 W/(m2K) and 111–240 W/(m2), for fuzzy logic and cluster renewal approach respectively. The divergence in calculated heat flux recovery along the furnace height between fuzzy logic and cluster renewal approach did not exceeded ±2%.