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Coal and biomass cofiring: CFD modeling 91

Testing for modeling
Heterogeneous validation Radiative heat
reaction module transfer module

Fluid transport module
Homogeneous Particle motion
(Mass, momentum, energy and
reaction module module
species conservation equations)
Pollutant Turbulence
formation module Ash behavior module
module
Figure 4.1 Computational fluid dynamics modeling of coal and biomass cofiring: An overview
of the basic modules.

CFD modeling of solid fuel combustion. When biomass is cofired, pollutant formation
(e.g., NO x emissions) and ash deposition also become important for the performance of
the cofiring systems, primarily due to the low ash melting temperatures of most
biomass fuels. The general modeling issues outlined in the seven bubbles are elabo-
rated in the following sections.

4.3.1 Turbulent mixing

Industrial cofiring processes always feature a turbulent flow. Mainly limited by the
computational resources, the major concerns of industrial cofiring CFD modeling
are still placed on the mean flow characteristics. Therefore, time-averaging is widely
used to eliminate turbulent fluctuations. The time-averaging of the fluid conservation
equations introduces extra turbulent flux terms, making the system of the equations no
longer closed. Turbulence models are needed. The commonly used turbulence models
under the Reynolds-averaged NaviereStokes (RANS) modeling framework assume
the Reynolds or turbulent stresses are analogous to the viscous stresses. Such turbu-
lence models account for the impact of the unresolved large-scale eddies on the
mean fluid flow to some extent and close the system of time-averaged fluid transport
equations.
With the advancement in computational power, large eddy simulation (LES) of coal
and biomass cofiring has received great interest from academia in the last decade,
which also spreads to industries now (Pitsch, 2006; Rabacal et al., 2014; Olenik
et al., 2015). Different from the RANS modeling, in which only the mean flow quan-
tities are resolved and the impact of the large-scale eddies on the mean flow is
modeled, LES directly resolves the large-scale motion of the turbulence. The large-
scale eddies, whose motion depends on the flow geometry, carry most of the turbulent
kinetic energy and control the dynamics of the turbulence. In LES, only the small-scale
subgrid eddies, which are universal and not dependent on individual flow geometry,
are modeled to account for their impact on the resolved large-scale eddies. As a result,
LES, combined with appropriate subgrid models for the small-scale eddies, greatly