Imperial College London
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ProfessorSylvainLaizet

Faculty of Engineering, Department of Aeronautics

Professor in Computational Fluid Mechanics
 
 
 
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Contact

 

+44 (0)20 7594 5045s.laizet Website

 
 
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Location

 

339City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{O'Connor:2024:10.1016/j.compfluid.2023.106108,
author = {O'Connor, J and Laizet, S and Wynn, A and Edeling, W and Coveney, P},
doi = {10.1016/j.compfluid.2023.106108},
journal = {Computers and Fluids},
title = {Quantifying uncertainties in direct numerical simulations of a turbulent channel flow},
url = {http://dx.doi.org/10.1016/j.compfluid.2023.106108},
volume = {268},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Direct numerical simulation (DNS) provides unrivalled levels of detail and accuracy for simulating turbulent flows. However, like all numerical methods, DNS is subject to uncertainties arising from the numerical scheme and input parameters (e.g. mesh resolution). While uncertainty quantification (UQ) techniques are being employed more and more to provide a systematic analysis of uncertainty for lower-fidelity models, their application to DNS is still relatively rare. In light of this, the aim of this work is to apply UQ and sensitivity analysis to the DNS of a canonical wall-bounded turbulent channel flow at low Reynolds number (Re = 180). To compute the DNS, Incompact3d – a highly scalable open-source framework based on high-order compact finite differences and a spectral Poisson solver – is used as a black-box solver. Stochastic collocation is used to propagate the input uncertainties through Incompact3d to the output quantities of interest (QOIs). To facilitate the non-intrusive forward UQ analysis, the open-source EasyVVUQ package is used to provide integrated capability for sampling, pre-processing, execution, post-processing, and analysis of the computational campaign. Three separate UQ campaigns are conducted. The first two examine the effect of domain size and the numerical parameters (e.g. mesh resolution, time step, sample time), respectively, and adopt Gaussian quadrature rules combined via tensor products to sample the multi-dimensional input space. Finally, the third campaign investigates the performance of a dimension-adaptive sampling strategy that significantly reduces the computational cost compared to the full tensor product approach. The analysis focuses on the cross-channel statistical moments of the QOIs, as well as local and global sensitivity analyses to assess the sensitivity of each QOI with respect to each individual input. This enables an assessment of the robustness and sensitivity of DNS to the user-defined numerical paramete
AU  - O'Connor,J
AU  - Laizet,S
AU  - Wynn,A
AU  - Edeling,W
AU  - Coveney,P
DO  - 10.1016/j.compfluid.2023.106108
PY  - 2024///
SN  - 0045-7930
TI  - Quantifying uncertainties in direct numerical simulations of a turbulent channel flow
T2  - Computers and Fluids
UR  - http://dx.doi.org/10.1016/j.compfluid.2023.106108
UR  - http://hdl.handle.net/10044/1/108010
VL  - 268
ER  -
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