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In Computational Fluid Dynamics (CFD) studies composed of the coupling ofdifferent simulations, the uncertainty in one stage may be propagated to thefollowing stage and affect the accuracy of the prediction. In this paper, aframework for uncertainty quantification is applied to the two-step simulationof the mechanical design of a swirling jet flow generated by a rotating pipe(\textit{Simulation 1}) impinging on a flat plate to provide convective heattransfer (\textit{Simulation 2}). The first approach is the StochasticCollocation Method (SCM) with Clenshaw-Curtis sparse grids. The conclusiondrawn from the analysis is that the simulated system does not exhibit asignificant sensitivity to stochastic variations of model input parameters,over the tested uncertainty ranges.  Additionally, a set of non-linear regression models for the stochasticvelocity and turbulent profiles for the pipe nozzle are created and tested,since impinging jets at Reynolds number of $Re=23000$ are very frequent in theliterature, but stochastic inlet conditions have never been provided. Numericalresults demonstrate a negligible difference in the predicted convective heattransfer with respect to the use of the profiles simulated via CFD. Thesesuggested surrogate models can be directly embedded onto other CFD applications(e.g arrays of jets or jet flows impinging on plates with different shapes) inwhich a realistic swirling flow under uncertainty can be of interest.

Propagation of Uncertainty in a Rotating Pipe Mechanism to Generate an Impinging Swirling Jet Flow for Heat Transfer from a Flat Plate