Propagation of Uncertainty in a Rotating Pipe Mechanism to Generate an Impinging Swirling Jet Flow for Heat Transfer from a Flat Plate
F.-J. Granados-Ortiz, J. Ortega-Casanova, C.-H. Lai

TL;DR
This study applies uncertainty quantification to a CFD simulation of a swirling jet impinging on a flat plate, finding minimal sensitivity to input variations and developing surrogate models for turbulent profiles.
Contribution
It introduces a framework for uncertainty propagation in swirling jet CFD simulations and creates surrogate models for stochastic inlet conditions.
Findings
System shows low sensitivity to input uncertainties.
Surrogate models accurately replicate stochastic velocity and turbulent profiles.
Negligible impact on heat transfer predictions under tested uncertainties.
Abstract
In Computational Fluid Dynamics (CFD) studies composed of the coupling of different simulations, the uncertainty in one stage may be propagated to the following stage and affect the accuracy of the prediction. In this paper, a framework for uncertainty quantification is applied to the two-step simulation of the mechanical design of a swirling jet flow generated by a rotating pipe (\textit{Simulation 1}) impinging on a flat plate to provide convective heat transfer (\textit{Simulation 2}). The first approach is the Stochastic Collocation Method (SCM) with Clenshaw-Curtis sparse grids. The conclusion drawn from the analysis is that the simulated system does not exhibit a significant sensitivity to stochastic variations of model input parameters, over the tested uncertainty ranges. Additionally, a set of non-linear regression models for the stochastic velocity and turbulent profiles for…
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Taxonomy
TopicsProbabilistic and Robust Engineering Design · Wind and Air Flow Studies · Nuclear Engineering Thermal-Hydraulics
