Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Fineness of Cement

Fineness of Cement

The fineness of cement directly influences the rate of hydration, as the hydration begins at the surface of the cement particles. In addition to hydration, the fineness of cement is vital for various properties of concrete including workability, gypsum requirement, and long-term behavior. The fineness of cement is represented in terms of the specific surface of cement which is typically measured in square meters per kilogram, with several methods available for this determination.
Direct...

Porosity in Cement Paste

Porosity in Cement Paste

The porosity of concrete is a measure of the void spaces within its structure. These spaces impact its strength and durability significantly. When water and cement interact, a chemical reaction called hydration creates a semi-solid paste. This paste includes combined water, making up approximately 23% of the cement's dry mass, and gel water, which fills minuscule voids known as gel pores, accounting for about 28% of the cement gel volume.
The balance of water to cement in the mix is...

Porosity and Absorption of Aggregate

Porosity and Absorption of Aggregate

Aggregates contain pores of varying sizes; while some are completely enclosed within the particles, others open onto the surface, allowing water to penetrate. The porosity of aggregates is a major factor contributing to the overall porosity of concrete, given that aggregates constitute about three-quarters of concrete's volume.
When all pores in an aggregate are filled with water, the aggregate is considered saturated and surface-dry. If left in dry air, water will evaporate until the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Golimumab for the Treatment of Rheumatoid Arthritis: A Narrative Review of Pivotal Randomized Trials and Real-World Studies.

Rheumatology and therapy·2026

Same author

Ejaculatory function after robotic waterjet ablation for the treatment of benign prostatic hyperplasia: a systematic review.

International journal of impotence research·2025

Same author

Drying-induced atomic structural rearrangements in sodium-based calcium-alumino-silicate-hydrate gel and the mitigating effects of ZrO<sub>2</sub> nanoparticles.

Physical chemistry chemical physics : PCCP·2018

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 7, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Automated estimation of cementitious sorptivity via computer vision.

Hossein Kabir¹, Jordan Wu², Sunav Dahal¹

¹Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

Nature Communications

|November 15, 2024

Summary

A new computer vision model automates water uptake monitoring in cementitious materials, providing real-time durability assessments. This method replaces traditional, labor-intensive weight measurements for improved construction material analysis.

More Related Videos

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ

Published on: December 16, 2019

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Related Experiment Videos

Last Updated: Jun 7, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ

Determination of Aggregate Surface Morphology at the Interfacial Transition Zone ITZ

Published on: December 16, 2019

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Area of Science:

Materials Science
Civil Engineering
Computer Vision

Background:

Monitoring water uptake is vital for assessing cementitious material durability against environmental factors.
Current methods like ASTM C1585 rely on manual, infrequent weight measurements, limiting real-time analysis.
Developing automated, accurate methods for water absorption monitoring is essential for construction material science.

Purpose of the Study:

To develop and validate a computer vision model for automated, real-time monitoring of water uptake in cementitious systems.
To replace labor-intensive traditional methods with an efficient, automated approach for durability assessment.
To enable accurate prediction of sorptivity values for enhanced material performance evaluation.

Main Methods:

A custom computer vision model was trained using 6234 images (4000 real, 2234 synthetic).
The model was trained on 1440 data points from 15 paste mixtures (w/c ratios 0.4-0.8, curing 1-7 days).
The model automatically detects water levels in prismatic samples, estimating water penetration every minute.

Main Results:

The computer vision model accurately predicts initial and secondary sorptivities in real time (R² > 0.9).
Achieved high confidence in predictions after training on diverse paste mixtures.
Demonstrated successful application on mortar and concrete systems.

Conclusions:

The developed computer vision model offers a low-cost, automated solution for monitoring water uptake.
This technology facilitates real-time durability assessment of construction materials.
Paves the way for improved quality control and material development in the construction industry.