Multi-fidelity uncertainty quantification of particle deposition in turbulent pipe flow

Yuan Yao; Xun Huan; Jesse Capecelatro

doi:10.1016/j.jaerosci.2022.106065

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arXiv · 2205.04979

Multi-fidelity uncertainty quantification of particle deposition in turbulent pipe flow

Yuan Yao·Xun Huan·Jesse Capecelatro

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Abstract

Particle deposition in fully-developed turbulent pipe flow is quantified taking into account uncertainty in electric charge, van der Waals strength, and temperature effects. A framework is presented for obtaining variance-based sensitivity in multiphase flow systems via a multi-fidelity Monte Carlo approach that optimally manages model evaluations for a given computational budget. The approach combines a high-fidelity model based on direct numerical simulation and a lower-order model based on a one-dimensional Eulerian description of the two-phase flow. Significant speedup is obtained compared to classical Monte Carlo estimation. Deposition is found to be most sensitive to electrostatic interactions and exhibits largest uncertainty for mid-sized (i.e., moderate Stokes number) particles.

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Yuan Yao, Xun Huan, Jesse Capecelatro. 2022-05-10. Multi-fidelity uncertainty quantification of particle deposition in turbulent pipe flow. https://doi.org/10.1016/j.jaerosci.2022.106065

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