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Modelling the stochastic nature of porosity in a respirator canister using computational fluid dynamics
Author(s) -
Wood Samuel G. A.,
Chakraborty Nilanjan,
Smith Martin W.,
Summers Mark J.
Publication year - 2021
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.23916
Subject(s) - porosity , mechanics , pressure drop , residence time (fluid dynamics) , turbulence , residence time distribution , reynolds number , reynolds averaged navier–stokes equations , particle size , flow (mathematics) , materials science , mathematics , geology , physics , geotechnical engineering , composite material , paleontology
Abstract A model has been developed to represent the stochastic nature of the activated carbon bed within a generic chemical biological radiological and nuclear (CBRN) respirator canister. The porous region is subdivided into discrete sections which are assigned a porosity based on their radial position according to a longitudinally‐averaged porosity model, and then perturbed by some amount according to a Gaussian distribution. The porosity model was used in Reynolds‐averaged Navier‐Stokes (RANS) simulations in order to assess the impacts that the choice of section size and the porosity variation would have on the pressure drop and residence time distribution. It was shown for small section sizes that increasing porosity variation would increase pressure drop and minimum residence time in the carbon bed, while decreasing the average residence time. As the section sizes became larger the reverse trend was seen as a greater extent of flow channelling throughout the bed became apparent. For the given domain size, there was an upper limit to the section size, beyond which statistical convergence could not be guaranteed. It was also shown that for section sizes close to the particle diameter, the results would depend only on the ratio of section size to porosity variation, reducing the porosity model to a single parameter. A few selected cases were simulated at higher flow rates, where the previously mentioned trends were seen to persist.