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Pore Size Distribution

Pore Size Distribution

In concrete, the pore size distribution significantly influences the material's properties. Capillary pores, markedly larger than gel pores, form a vast network within partially hydrated cement paste, reducing the concrete's strength and increasing its permeability. This heightened permeability leads to a greater risk of damage from environmental factors like freeze-thaw cycles and chemical attacks, with the extent of vulnerability also being tied to the water-to-cement ratio.
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Related Experiment Video

Updated: Jan 10, 2026

Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders

Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders

Published on: December 4, 2020

3D pore shape is predictable in randomly packed particle systems.

Yasha Saxena¹, Lindsay Riley¹, Runxin Wu¹

¹Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA.

|November 21, 2025

Summary

This summary is machine-generated.

This study classifies 3D pore shapes in granular materials using KNN, revealing octahedron (O) and icosahedron (I) pore types. These pore geometries influence fluid dynamics and can be tuned by altering particle properties.

Keywords:

Random packing complex systems dimensionality reduction flow granular materials material characterization microstructure pore classification pore structure shape classification

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Area of Science:

Geology
Materials Science
Fluid Dynamics

Background:

Pore size is insufficient for understanding 3D transport in granular materials.
Geometric classification of 3D pores is crucial for linking pore structure to material function.
Existing methods often overlook detailed shape characteristics.

Purpose of the Study:

To implement a KNN-based classification for 3D pores focusing on shape properties.
To compare pore geometries in random and ideal hexagonal packing.
To investigate the impact of pore shape on fluid dynamics and how to control pore distribution.

Main Methods:

K-Nearest Neighbors (KNN) algorithm for pore classification.
Analysis of pore geometry in randomly and hexagonally packed granular systems.
Computational fluid dynamics (CFD) simulations to assess transport phenomena.
Parametric studies on particle properties (shape, stiffness, size) to tune pore distribution.

Main Results:

Pore types in random packing mirror those in ideal hexagonal packing.
Octahedron (O) and Icosahedron (I) are dominant pore configurations in both systems.
Distinct fluid dynamic behaviors were observed between different pore types during flow simulations.
O/I pore distribution is tunable via modification of particle characteristics.

Conclusions:

3D pore shape is a critical factor in granular material behavior, beyond mere size.
The KNN approach effectively classifies pores based on shape, offering insights into transport.
Understanding and controlling pore geometry (O/I distribution) can inform the design of granular systems for specific applications.