Imperial College London
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DrMichaelBluck

Faculty of Engineering, Department of Mechanical Engineering

Reader in Nuclear Engineering
 
 
 
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Contact

 

+44 (0)20 7594 7055m.bluck

 
 
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Location

 

658City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Duan:2021:10.1016/j.nucengdes.2021.111307,
author = {Duan, Y and Ahn, JS and Eaton, MD and Bluck, MJ},
doi = {10.1016/j.nucengdes.2021.111307},
journal = {Nuclear Engineering and Design},
pages = {1--12},
title = {Quantification of the uncertainty within a SAS-SST simulation caused by the unknown high-wavenumber damping factor},
url = {http://dx.doi.org/10.1016/j.nucengdes.2021.111307},
volume = {381},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper aims to quantify the uncertainty in the SAS-SST simulation of a prism bluff-body flow due to varyingthe higher-wavenumber damping factor (Cs). Instead of performing the uncertainty quantification on the CFDsimulation directly, a surrogate modelling approach is adopted. The mesh sensitivity is first studied and thenumerical error due to the mesh is approximated accordingly. The Gaussian processes/Kriging method is used togenerate surrogate models for quantities of interest (QoIs). The suitability of the surrogate models is assessedusing the leave-one-out cross-validation tests (LOO-CV). The stochastic tests are then performed using the crossvalidated surrogate models to quantify the uncertainty of QoIs by varying Cs. Four prior probability densityfunctions (such as U(0, 1), N(0.5, 0.12), Beta(2, 2) and Beta(5, 1.5)) of Cs are considered.It is demonstrated in this study that the uncertainty of a predicted QoI due to varying Cs is regionallydependent. The flow statistics in the near wake of the prism body are subject to larger variance due to theuncertainty in Cs. The influence of Cs rapidly decays as the location moves downstream. The response of differentQoIs to the changing Cs varies greatly. Therefore, the calibration of Cs only using observations of one variablemay bias the results. Last but not least, it is important to consider different sources of uncertainties within thenumerical model when scrutinising a turbulence model, as ignoring the contributions to the total error may leadto biased conclusions.
AU  - Duan,Y
AU  - Ahn,JS
AU  - Eaton,MD
AU  - Bluck,MJ
DO  - 10.1016/j.nucengdes.2021.111307
EP  - 12
PY  - 2021///
SN  - 0029-5493
SP  - 1
TI  - Quantification of the uncertainty within a SAS-SST simulation caused by the unknown high-wavenumber damping factor
T2  - Nuclear Engineering and Design
UR  - http://dx.doi.org/10.1016/j.nucengdes.2021.111307
UR  - https://www.sciencedirect.com/science/article/pii/S0029549321002594?via%3Dihub
UR  - http://hdl.handle.net/10044/1/89810
VL  - 381
ER  -
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