Towards replacing physical testing of granular materials with a Topology-based Model
Aniketh Venkat, Attila Gyulassy, Graham Kosiba, Amitesh Maiti, Henry, Reinstein, Richard Gee, Peer-Timo Bremer, and Valerio Pascucci

TL;DR
This paper introduces a topology-based virtual modeling approach to replace physical testing of granular materials, improving accuracy in flow and permeability predictions across diverse particle shapes and sizes.
Contribution
The study develops a novel Pore Network Model using Morse-Smale complex skeletons to simulate fluid flow in granular materials based on micro-CT images, bypassing traditional physical tests.
Findings
The model accurately predicts flow conductance in complex granular structures.
It provides consistent permeability estimates across varied particle geometries.
The approach reduces reliance on physical permeametry tests.
Abstract
In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The "effective surface area," the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements…
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Taxonomy
TopicsTopological and Geometric Data Analysis · Groundwater flow and contamination studies · Hydrocarbon exploration and reservoir analysis
