  A stochastic approach based on generalized Polynomial Chaos (gPC) is used to
quantify the error in Large-Eddy Simulation (LES) of a spatially-evolving
mixing layer flow and its sensitivity to different simulation parameters, viz.
the grid stretching in the streamwise and lateral directions and the subgrid
scale model constant ($C_S$). The error is evaluated with respect to the
results of a highly resolved LES (HRLES) and for different quantities of
interest, namely the mean streamwise velocity, the momentum thickness and the
shear stress. A typical feature of the considered spatially evolving flow is
the progressive transition from a laminar regime, highly dependent on the inlet
conditions, to a fully-developed turbulent one. Therefore the computational
domain is divided in two different zones (\textit{inlet dependent} and
\textit{fully turbulent}) and the gPC error analysis is carried out for these
two zones separately. An optimization of the parameters is also carried out for
both these zones. For all the considered quantities, the results point out that
the error is mainly governed by the value of the $C_S$ constant. At the end of
the inlet-dependent zone a strong coupling between the normal stretching ratio
and the $C_S$ value is observed. The error sensitivity to the parameter values
is significantly larger in the inlet-dependent upstream region; however, low
error values can be obtained in this region for all the considered physical
quantities by an ad-hoc tuning of the parameters. Conversely, in the turbulent
regime the error is globally lower and less sensitive to the parameter
variations, but it is more difficult to find a set of parameter values leading
to optimal results for all the analyzed physical quantities.
