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Computational Multiphysics Research Group
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  1. Computational Multiphysics Research Group
  2. Research

Applied & Industrial

Biodegradation of Gasoline Compounds in the Subsurface

Professor Unger is working in collaboration with Robert Enouy to enhance CompFlow BioF to include biodegradation of gasoline components (and other substrates) in the subsurface under aerobic and anaerobic conditions. Novel contributions include a diffusive-flux implementation of alliteratively limiting electron donor and accepter conditions during microbial growth (first panel). This dynamic mass transport mechanism moves beyond the restrictions of Monod conditions and permits simulation the sparging of oxygenated air in heterogenous aquifers to stimulate biomass growth (second panel) and replenish oxygen in both the aqueous and gas phases above and below the water table (third panel).

Novel contributions include a diffusive-flux implementation of alliteratively limiting electron donor and accepter conditions during microbial growth

This dynamic mass transport mechanism moves beyond the restrictions of Monod conditions and permits simulation the sparging of oxygenated air in heterogenous aquifers to stimulate biomass growthReplenish oxygen in both the aqueous and gas phases above and below the water table

Pore Network Modelling of Multiphysics in Electrochemical Devices

The performance of electrochemical devices such as batteries depends heavily on the structure of the porous electrodes found in batteries.  Incorporating the physical structure into device simulations is not generally possible with traditional modeling framework due to enormous computational cost.  Professors Jeff Gostick and Marios Ioannidis have pioneered and developed an approach known as pore network modeling that abstracts the porous media an equivalent resistor network [1].  This reduces the computational complexity by more than 10,000X thereby allowing complex multiphysics simulations of battery performance, which inherently include the impact of structure via the topology and geometry of the network.  This approach was originally developed for modeling multiphase flow in geological materials, but Prof’s Gostick and Ioannidis have extended it to non-conventional materials found in electrodes [2].  Prof. Gostick has also been actively involved in the development of OpenPNM [3], the leading open source software package for conducting pore network simulations, which has recently received substantial funding from CANARIE to further develop it features and enhance it’s usability.  The figure on the left shows a pore network model indicated by the sphere, overlaid on an artificially generated fibrous structure.  The figure on the right, shows a multiphase diffusion simulation on the same network with blue indicating the locations on invading water and the color map showing the local gas concentration.

[1]  Ioannidis, M.A, I. Chatzis, Network modelling of pore structure and transport properties of porous media, Chemical Engineering Science 48 (5), 951-972 (1993)

[2] Gostick, J., M.A. Ioannidis, M.W. Fowler, and M.D. Pritzker, Pore network modeling of fibrous gas diffusion layers for polymer electrolyte membrane fuel cells. Journal of Power Sources. 173: p. 277-290 (2007)

[3] Gostick, J.*, M. Aghighi, J. Hinebaugh, T. Tranter, M.A. Hoeh, H. Day, B. Spellacy, M. Sharqawy, A. Bazylak, A. Burns, W. Lehnert and A. Putz. OpenPNM: A Pore Network Modeling Package. Computing in Science & Engineering. 18(4), p60-74 (2016)

Pore Network Modelling of Multiphysics in Electrochemical DevicesPore Network Modelling of Multiphysics in Electrochemical Devices

Quantitative Analysis of Volumetric Images of Fibrous Electrodes

Professor Gostick is working with several international research groups on the manufacture, testing and characterization of flow battery electrodes.  Computed x-ray tomography images, also known as cat-scans, have been obtained by Professors Paul Shearing, Dan Brett and Rhodri Jervis at University College London, and Prof. Gostick’s group has been developing numerical tools for extracting key structural information from them.  The figure on the left shows a pore size estimation filter applied to an electrode produced in Prof Gostick’s lab by electrospinning [1]. The color corresponds to the radius (in voxels) of the largest sphere that can be drawn within the pore space.  This image based approach removes the need for complex interpretation of porosimetry curves and also provides information about the spatial distribution or correlation of pores sizes [2].  The figure on the right shows a pore network overlaid onto an image of a commercial fibrous electrode.  The ability to analyze the pore space as an abstract network vastly reduces the computational demands and even enables the simulation of device performance including multiphysics and multiphase flow.

[1]  Liu, S, MDR Kok, YW Kim, JL Baron, FR Brushett, JT Gostick*, Evaluation of Electrospun Fibrous Mats Targeted for Use as Flow Battery Electrodes. J. Electrochem. Soc. 164, A2038–A2048 (2017)

[2] Kok, M.D.R., R. Jervis, P.R. Shearing, D. Brett, and J. Gostick*, Insights into the Effect of Structural Heterogeneity in Carbonized Electrospun Fibrous Mats for Flow Battery Electrodes by X-Ray Tomography. Small. 14(9), 1703616 (2018)

[3] Gostick, J. T. Versatile and efficient pore network extraction method using marker-based watershed segmentation. Phys. Rev. E 96, 023307 (2017)

Quantitative Analysis of Volumetric Images of Fibrous ElectrodesQuantitative Analysis of Volumetric Images of Fibrous Electrodes

Three-Phase Flow in Discretely Fracture Porous Rock

Professor Unger is working Professor Beth Parker, in collaboration with Ken Walton at the University of Guelph to extended the multi-phase compositional software CompFlow BioF to simulate oil-water-gas phase migration in discretely fractured porous rock. Fracture networks can be 2D and 3D and can consists of many thousands of intersecting fractures. Applications include simulating the migration of oil from the surface down through the vadose zone, capillary fringe and then beneath the water table. The figure on the left shows steady-state water saturations before the oil spill, while the figure on the right shows oil saturations two years after 1 barrel of oil is released in the domain.

Three-phase flow in discretely fracture porous rock Three-phase flow in discretely fracture porous work

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Computational multiphysics research group
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