Assessment of predictive capability of hybrid URANS/LES methods in residence time calculation
Assessment of predictive capability of hybrid URANS/LES methods in residence time calculation
The present study aims to assess capability of mostly used hybrid URANS/LES methods in dealing with a complex swirled configuration/reactor when the residence time characteristics need to be predicted at acceptable level of accuracy and fidelity. The configuration is quite complex and out of reach of the classical RANS turbulence models as it consists of different, partly swirled inlet channels and a large variety of time and length scales. In this work only the flow field is considered and is investigated using three different hybrid URANS/LES simulation methods. The models: the Scale Adaptive Simulation (SAS), the Improved Delayed Detached Eddy Simulation(SA-IDDES) and the
, use different triggering mechanisms and underlying RANS models. The results of the flow field, the residence time characteristics and all related quantities are compared with both the Large Eddy Simulation (LES) and experimental data reported in Doost et al. (2016). It turns out that none of the considered hybrid methods is able to predict the residence time characteristics as well as LES does mainly due to the inaccurate prediction of the flow field. It was found that there is a need to improve the hybrid approaches by addressing the shortcomings, particularly those regarding triggering mechanism to make hybrid approaches a reliable computational tool for study complex turbulent flows inside full scale configurations where LES can be prohibitively expensive.
Mehdizadeh, A.
48437b9b-1de9-45fc-8683-5069f384e5a9
Doost, S.
ccfcbe4e-8bea-4e2f-9b6b-623c9c3eba6a
Sadiki, A.
a7e115c9-1474-4591-bdf5-765c77763eb3
Janicka, J.
f05f910e-fc95-4c96-a6e4-8d733e188958
Karimi, N.
620646d6-27c9-4e1e-948f-f23e4a1e773a
Mehdizadeh, A.
48437b9b-1de9-45fc-8683-5069f384e5a9
Doost, S.
ccfcbe4e-8bea-4e2f-9b6b-623c9c3eba6a
Sadiki, A.
a7e115c9-1474-4591-bdf5-765c77763eb3
Janicka, J.
f05f910e-fc95-4c96-a6e4-8d733e188958
Karimi, N.
620646d6-27c9-4e1e-948f-f23e4a1e773a
Mehdizadeh, A., Doost, S., Sadiki, A., Janicka, J. and Karimi, N.
(2018)
Assessment of predictive capability of hybrid URANS/LES methods in residence time calculation.
Chemical Engineering Science.
(doi:10.1016/j.ces.2018.02.035).
Abstract
The present study aims to assess capability of mostly used hybrid URANS/LES methods in dealing with a complex swirled configuration/reactor when the residence time characteristics need to be predicted at acceptable level of accuracy and fidelity. The configuration is quite complex and out of reach of the classical RANS turbulence models as it consists of different, partly swirled inlet channels and a large variety of time and length scales. In this work only the flow field is considered and is investigated using three different hybrid URANS/LES simulation methods. The models: the Scale Adaptive Simulation (SAS), the Improved Delayed Detached Eddy Simulation(SA-IDDES) and the
, use different triggering mechanisms and underlying RANS models. The results of the flow field, the residence time characteristics and all related quantities are compared with both the Large Eddy Simulation (LES) and experimental data reported in Doost et al. (2016). It turns out that none of the considered hybrid methods is able to predict the residence time characteristics as well as LES does mainly due to the inaccurate prediction of the flow field. It was found that there is a need to improve the hybrid approaches by addressing the shortcomings, particularly those regarding triggering mechanism to make hybrid approaches a reliable computational tool for study complex turbulent flows inside full scale configurations where LES can be prohibitively expensive.
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e-pub ahead of print date: 8 March 2018
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Local EPrints ID: 508870
URI: http://eprints.soton.ac.uk/id/eprint/508870
ISSN: 0009-2509
PURE UUID: 1b32fe0a-2a48-45af-98e7-efff91311b20
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Date deposited: 05 Feb 2026 17:42
Last modified: 06 Feb 2026 03:12
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Author:
A. Mehdizadeh
Author:
S. Doost
Author:
A. Sadiki
Author:
J. Janicka
Author:
N. Karimi
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