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Predicting vapour transport from semi-volatile organic compounds concealed within permeable packaging

Predicting vapour transport from semi-volatile organic compounds concealed within permeable packaging
Predicting vapour transport from semi-volatile organic compounds concealed within permeable packaging
The vapour concentration present in enclosed spaces containing concealed semi-volatile organic compounds (SVOCs), such as explosives, is difficult to measure experimentally. Therefore, mathematical models play a key role in understanding the transport of these materials. Vapour transport has previously been modelled in a range of environments, from small emission cells to whole rooms, using both analytical and numerical approaches. These models typically include either a well-mixed air volume or a simple sorption model. This work has been extended by including a multi-layer vapour sorption/permeation model within a computational fluid dynamics (CFD) framework. This allows for vapour source terms from items concealed within permeable packaging to be considered. The CFD based permeation model includes sorption/desorption, using a linear isotherm at inner and outer surfaces and a blended wall function to account for the effects of near-wall turbulence. The model has been validated for the explosive SVOC, ethylene glycol dinitrate (EGDN). The model has been used to show how vapour concentrations around a cardboard box containing a SVOC vary when some of the key input parameters are changed. Changing the vapour source from EGDN to the much lower vapour pressure trinitrotoluene (TNT), had a significant effect, as expected, and this was most pronounced early on due to the difference in permeation lag times for the two materials. Conversely, changing the type of cardboard had only a small effect on the concentrations. This type of modelling approach can now be used to study a wide range of SVOC transport problems which would not previously have been possible.
Computational fluid dynamics, Detection, Explosives, Permeation, SVOC, Sorption
0017-9310
Foat, Timothy, Graham
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Drodge, Joseph
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Charleson, Alexandra
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Whatmore, Barry
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Pownall, Sophie
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Glover, Peter
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Nally, James
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Parker, Simon
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Khan, Catherine
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Marr, Andrew
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Foat, Timothy, Graham
eddebff8-0a58-4a9a-a2ec-45563e965245
Drodge, Joseph
8dc950e9-1166-4499-8d20-88735cef6d0f
Charleson, Alexandra
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Whatmore, Barry
09b6aea8-a5e4-481a-8f87-08fd3032a80b
Pownall, Sophie
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Glover, Peter
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Nally, James
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Parker, Simon
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Khan, Catherine
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Marr, Andrew
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Foat, Timothy, Graham, Drodge, Joseph, Charleson, Alexandra, Whatmore, Barry, Pownall, Sophie, Glover, Peter, Nally, James, Parker, Simon, Khan, Catherine and Marr, Andrew (2021) Predicting vapour transport from semi-volatile organic compounds concealed within permeable packaging. International Journal of Heat and Mass Transfer, 183 (part A), [122012]. (doi:10.1016/j.ijheatmasstransfer.2021.122012).

Record type: Article

Abstract

The vapour concentration present in enclosed spaces containing concealed semi-volatile organic compounds (SVOCs), such as explosives, is difficult to measure experimentally. Therefore, mathematical models play a key role in understanding the transport of these materials. Vapour transport has previously been modelled in a range of environments, from small emission cells to whole rooms, using both analytical and numerical approaches. These models typically include either a well-mixed air volume or a simple sorption model. This work has been extended by including a multi-layer vapour sorption/permeation model within a computational fluid dynamics (CFD) framework. This allows for vapour source terms from items concealed within permeable packaging to be considered. The CFD based permeation model includes sorption/desorption, using a linear isotherm at inner and outer surfaces and a blended wall function to account for the effects of near-wall turbulence. The model has been validated for the explosive SVOC, ethylene glycol dinitrate (EGDN). The model has been used to show how vapour concentrations around a cardboard box containing a SVOC vary when some of the key input parameters are changed. Changing the vapour source from EGDN to the much lower vapour pressure trinitrotoluene (TNT), had a significant effect, as expected, and this was most pronounced early on due to the difference in permeation lag times for the two materials. Conversely, changing the type of cardboard had only a small effect on the concentrations. This type of modelling approach can now be used to study a wide range of SVOC transport problems which would not previously have been possible.

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Accepted/In Press date: 23 September 2021
e-pub ahead of print date: 20 October 2021
Additional Information: Funding Information: The Fluent UDFs were written by Graham Macpherson, Dougal Ranford and Samuel Tabor of Frazer-Nash Consultancy Ltd. through a contract with Riskaware Ltd. We would like to acknowledge Megan Abbott, Monika Jurcic and Hannah McGinness for their work on the validation experiments and Steven Hawkins for his work on the UDFs. Timothy Foat would like to acknowledge the support of the Ph.D. scheme in the Faculty of Engineering and Physical Sciences at the University of Southampton. Crown Copyright ?[2021] Published by Elsevier Ireland Ltd. This is an open access article under the Open Government Licence (OGL) http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3. Publisher Copyright: © 2021 Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: Computational fluid dynamics, Detection, Explosives, Permeation, SVOC, Sorption

Identifiers

Local EPrints ID: 452517
URI: http://eprints.soton.ac.uk/id/eprint/452517
ISSN: 0017-9310
PURE UUID: c3d9e84c-0a08-438d-92fa-30c31a9caacc
ORCID for Timothy, Graham Foat: ORCID iD orcid.org/0000-0001-7514-9385

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Date deposited: 11 Dec 2021 11:25
Last modified: 16 Mar 2024 14:30

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Contributors

Author: Timothy, Graham Foat ORCID iD
Author: Joseph Drodge
Author: Alexandra Charleson
Author: Barry Whatmore
Author: Sophie Pownall
Author: Peter Glover
Author: James Nally
Author: Simon Parker
Author: Catherine Khan
Author: Andrew Marr

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