Image processing of computed tomography scanned poly-dispersed beds for computational fluid dynamic studies
Image processing of computed tomography scanned poly-dispersed beds for computational fluid dynamic studies
Achieving our emission reduction goals requires the bulk production of carbon-neutral fuels and chemicals, which are catalytically produced through heterogeneous fixed bed chemical reactors. To optimise and scale-up these reactors, accurate and validated Computational Fluid Dynamics (CFD) models are crucial. Of especial importance to CFD simulations is the accurate depiction of the 3D bed structure used during the experimental setup. A direct one-to-one coupling between experiments and simulations can be achieved by scanning the experimental bed using computed tomography and reconstructing the scanned images as a 3D geometry for CFD simulations. However, processing of the scanned images is necessary to minimise highly coarse features that could impact the overall mesh size. A highly poly-dispersed lab-scale fixed bed reactor, previously scanned and analysed, is processed using various image-processing operations. Depending on the number and the crudeness of the processing operations, the bed is progressively deformed, which impacts both its porosity and its interparticle pore connectivity. The impact of image-processing becomes more evident when the hydrodynamic behaviour, i.e., X-, Y-, and Z-velocity and static pressure, of the beds is explored. CFD simulations revealed highly heterogeneous flow profiles, with the maximum velocity reached being 16-times higher than the average superficial velocity within the bed. Moreover, small modifications in local topological features introduce significant changes to the flow profiles, while the 3D pore interconnectivity was seen to play an equally important role as the interparticle porosity. A particle size study revealed that large particles form less interconnected networks with higher pore volumes, which significantly reduce the flow velocity and the pressure drop experienced by the flow. The generated results yield key insights towards a deeper understanding of the behaviour of fixed bed chemical reactors, highly valuable for catalyst and reactor engineering.
Computational fluid dynamics (CFD), Computed-tomography (CT) scans, Fixed bed chemical reactors, Image processing, Poly-dispersed catalytic beds
Kyrimis, Stylianos
c58fb1be-3a2a-4231-bf5e-b49f1439cd4a
Raja, Robert
74faf442-38a6-4ac1-84f9-b3c039cb392b
Armstrong, Lindsay Marie
db493663-2457-4f84-9646-15538c653998
November 2023
Kyrimis, Stylianos
c58fb1be-3a2a-4231-bf5e-b49f1439cd4a
Raja, Robert
74faf442-38a6-4ac1-84f9-b3c039cb392b
Armstrong, Lindsay Marie
db493663-2457-4f84-9646-15538c653998
Kyrimis, Stylianos, Raja, Robert and Armstrong, Lindsay Marie
(2023)
Image processing of computed tomography scanned poly-dispersed beds for computational fluid dynamic studies.
Advanced Powder Technology, 34 (11), [104199].
(doi:10.1016/j.apt.2023.104199).
Abstract
Achieving our emission reduction goals requires the bulk production of carbon-neutral fuels and chemicals, which are catalytically produced through heterogeneous fixed bed chemical reactors. To optimise and scale-up these reactors, accurate and validated Computational Fluid Dynamics (CFD) models are crucial. Of especial importance to CFD simulations is the accurate depiction of the 3D bed structure used during the experimental setup. A direct one-to-one coupling between experiments and simulations can be achieved by scanning the experimental bed using computed tomography and reconstructing the scanned images as a 3D geometry for CFD simulations. However, processing of the scanned images is necessary to minimise highly coarse features that could impact the overall mesh size. A highly poly-dispersed lab-scale fixed bed reactor, previously scanned and analysed, is processed using various image-processing operations. Depending on the number and the crudeness of the processing operations, the bed is progressively deformed, which impacts both its porosity and its interparticle pore connectivity. The impact of image-processing becomes more evident when the hydrodynamic behaviour, i.e., X-, Y-, and Z-velocity and static pressure, of the beds is explored. CFD simulations revealed highly heterogeneous flow profiles, with the maximum velocity reached being 16-times higher than the average superficial velocity within the bed. Moreover, small modifications in local topological features introduce significant changes to the flow profiles, while the 3D pore interconnectivity was seen to play an equally important role as the interparticle porosity. A particle size study revealed that large particles form less interconnected networks with higher pore volumes, which significantly reduce the flow velocity and the pressure drop experienced by the flow. The generated results yield key insights towards a deeper understanding of the behaviour of fixed bed chemical reactors, highly valuable for catalyst and reactor engineering.
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Accepted/In Press date: 8 August 2023
Published date: November 2023
Additional Information:
Funding Information:
The authors would like to thank the Industrial Decarbonisation Research and Innovation Centre (IDRIC), grant number EP/V027050/1, for their funding. In addition, the authors would like to acknowledge the use of the IRIDIS 5 High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. Finally, we would like to thank Kathryn E. Rankin and Siul Ruiz for their help with Simpleware and geometry meshing.
Keywords:
Computational fluid dynamics (CFD), Computed-tomography (CT) scans, Fixed bed chemical reactors, Image processing, Poly-dispersed catalytic beds
Identifiers
Local EPrints ID: 482064
URI: http://eprints.soton.ac.uk/id/eprint/482064
ISSN: 0921-8831
PURE UUID: 1a1e7c87-9420-4a6f-bc5f-50edd0051afc
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Date deposited: 18 Sep 2023 16:51
Last modified: 18 Mar 2024 03:04
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Author:
Stylianos Kyrimis
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