Quantification of Total Porosity from CT Images by Segmenting Unhydrated Cement: A Model-Informed Framework Integrating POWERS’ Volume Model
Haoran Liu, Eryu Zhu, Min Ji, Zhengwei Bai, Teng Li

TL;DR
This paper introduces a new method to measure total porosity in cement using CT scans by combining a hydration model with image analysis.
Contribution
A novel model-informed framework that integrates Powers’ hydration model with micro-CT analysis to quantify total porosity in cement.
Findings
Total porosity of cement pastes ranged from 36.5% to 60.3% as w/c ratio increased from 0.4 to 0.7.
CT-derived porosity showed strong correlation (R2 > 0.98) with established porosity–strength models.
The method enables micro-CT to be used for quantitative microstructural analysis of cementitious materials.
Abstract
Quantification of total porosity, including the nano-scale fraction, is critical for predicting the performance of cement-based materials but remains a significant challenge. While X-ray computed tomography (CT) is a powerful non-destructive tool, a fundamental trade-off between resolution and representative sample volume prevents the direct segmentation of nano-scale pores in macroscopically relevant specimens. Herein, we propose and validate a novel model-informed framework that overcomes this limitation by integrating the classical Powers’ hydration model with micro-CT analysis. The method circumvents the need for nano-scale resolution by deriving the total porosity from the volume fraction of the easily segmentable, micron-scale unhydrated cement phase. The framework’s validity was demonstrated by showing a strong correlation between the CT-derived total porosity and established…
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Taxonomy
TopicsConcrete and Cement Materials Research · Enhanced Oil Recovery Techniques · Composite Material Mechanics
