  Simulations of pulverised coal combustion rely on various models, required in
order to correctly approximate the flow, chemical reactions, and behavior of
solid particles. These models, in turn, rely on multiple model parameters,
which are determined through experiments or small-scale simulations and contain
a certain level of uncertainty. The competing effects of transport, particle
physics, and chemistry give rise to various scales and disparate dynamics,
making it a very challenging problem to analyse. Therefore, the steady
combustion process of a single solid particle is considered as a starting point
for this study. As an added complication, the large number of parameters
present in such simulations makes a purely forward approach to sensitivity
analysis very expensive and almost infeasible. Therefore, the use of
adjoint-based algorithms, to identify and quantify the underlying sensitivities
and uncertainties, is proposed. This adjoint framework bears a great advantage
in this case, where a large input space is analysed, since a single forward and
backward sweep provides sensitivity information with respect to all parameters
of interest. In order to investigate the applicability of such methods, both
discrete and continuous adjoints are considered, and compared to the
conventional approaches, such as finite differences, and forward sensitivity
analysis. Various quantities of interest are considered, and sensitivities with
respect to the relevant combustion parameters are reported for two different
freestream compositions, describing air and oxy-atmospheres. This study serves
as a benchmark for future research, where unsteady and finally turbulent cases
will be considered.
