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A stochastic approach based on generalized Polynomial Chaos (gPC) is used toquantify the error in Large-Eddy Simulation (LES) of a spatially-evolvingmixing layer flow and its sensitivity to different simulation parameters, viz.the grid stretching in the streamwise and lateral directions and the subgridscale model constant ($C_S$). The error is evaluated with respect to theresults of a highly resolved LES (HRLES) and for different quantities ofinterest, namely the mean streamwise velocity, the momentum thickness and theshear stress. A typical feature of the considered spatially evolving flow isthe progressive transition from a laminar regime, highly dependent on the inletconditions, to a fully-developed turbulent one. Therefore the computationaldomain is divided in two different zones (\textit{inlet dependent} and\textit{fully turbulent}) and the gPC error analysis is carried out for thesetwo zones separately. An optimization of the parameters is also carried out forboth these zones. For all the considered quantities, the results point out thatthe error is mainly governed by the value of the $C_S$ constant. At the end ofthe inlet-dependent zone a strong coupling between the normal stretching ratioand the $C_S$ value is observed. The error sensitivity to the parameter valuesis significantly larger in the inlet-dependent upstream region; however, lowerror values can be obtained in this region for all the considered physicalquantities by an ad-hoc tuning of the parameters. Conversely, in the turbulentregime the error is globally lower and less sensitive to the parametervariations, but it is more difficult to find a set of parameter values leadingto optimal results for all the analyzed physical quantities.

Quantification of errors in large-eddy simulations of a spatially-evolving mixing layer