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In Situ Monitoring of Diffusion of Guest Molecules in Porous Media Using Electron Paramagnetic Resonance Imaging
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Statistical Effective Diffusivity Estimation in Porous Media Using an Integrated On-site Imaging Workflow for
James Le Houx1, Siul Ruiz2, Daniel McKay Fletcher2,3
1Department, Diamond Light Source, Harwell Science and Innovation Campus, Fermi Ave, Didcot, Oxfordshire OX11 0DE UK.
Transport in Porous Media
|September 4, 2023
Summary
This study enhances OpenImpala for faster, accurate estimation of porous media transport parameters. The improved model provides agile, bulk-scale effective diffusivity, crucial for real-time synchrotron imaging analysis.
Area of Science:
- Porous media physics
- Computational modeling
- Synchrotron imaging
Background:
- Transport in porous media is vital across many scientific and engineering fields.
- Image-based modeling offers detailed pore-scale insights but is computationally intensive.
- Real-time, bulk-scale parameter estimation is needed for efficient imaging campaigns.
Purpose of the Study:
- To enhance the OpenImpala image-based model solver.
- To enable fast estimation of bulk-scale effective transport parameters, specifically effective diffusivity.
- To validate the enhanced model's accuracy and computational speed against established methods.
Main Methods:
- Modified OpenImpala's boundary conditions and equations for multi-scale homogenization.
- Estimated effective pore space diffusivity across various elementary volume sizes.
- Validated results against COMSOL Multiphysics and compared computational performance.
Main Results:
- OpenImpala accurately estimated effective diffusivity, comparable to COMSOL.
- Homogenized domains using effective diffusivity showed less than 2% error compared to full models.
- OpenImpala simulations were two orders of magnitude faster than COMSOL.
Conclusions:
- The enhanced OpenImpala provides a fast and agile tool for assessing porous media.
- It is suitable for on-site tomography processing pipelines at synchrotron beamlines.
- The model aids in guiding imaging campaigns in real-time.
