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Total Voids in Concrete

Total Voids in Concrete

Total voids in concrete encompass gel water volume, capillary pores, and entrapped air. Gel water (retained within the cement hydration products) and physically entrapped or adsorbed water are significant for the hydration process. For complete hydration, it's estimated that the space needed for the products of a cubic centimeter of cement doubles. Capillary pores constitute the unoccupied space within the hydrated cement paste, with their size largely influenced by the water-to-cement...

Specific Gravity of Aggregate

Specific Gravity of Aggregate

Aggregates typically contain pores, which can be either permeable or impermeable. Considering the pores in the aggregates, the specific gravity of aggregates is defined in three different forms, namely, bulk or gross specific gravity, apparent specific gravity, and absolute specific gravity.
Bulk or gross specific gravity is calculated by taking the ratio of the mass of aggregates in the saturated surface-dry state to the total volume that includes both the solids and the voids within the...

Bulk Density of Aggregate

Bulk Density of Aggregate

Bulk density refers to the mass of aggregate particles that would fill a unit volume. The concept of bulk density originates from the inability to pack aggregate particles in a manner that completely eliminates void spaces. Hence, the term bulk refers to the volume that encompasses both the aggregates and the voids. This measurement is crucial when aggregates are batched by volume and is used to convert quantities by mass to volume.
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Porosity and Absorption of Aggregate

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Moisture Content and Bulking of Aggregate

Moisture Content and Bulking of Aggregate

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Related Experiment Video

Updated: Jan 3, 2026

Combined Size and Density Fractionation of Soils for Investigations of Organo-Mineral Interactions

Combined Size and Density Fractionation of Soils for Investigations of Organo-Mineral Interactions

Published on: February 15, 2019

A dataset on void ratio limits and their range for cohesionless soils.

Makbule Ilgac¹, Gizem Can¹, Kemal Onder Cetin¹

¹Dept. of Civil Engineering, Middle East Technical University, Ankara, Turkey.

|November 26, 2019

Summary

A comprehensive database of soil properties, including void ratios and particle characteristics, was compiled. This dataset, comprising 636 samples, will be used to develop predictive models for soil void ratios.

Keywords:

Coefficient of uniformity Mean grain size Void ratio

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Combined Size and Density Fractionation of Soils for Investigations of Organo-Mineral Interactions

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Area of Science:

Geotechnical Engineering
Soil Mechanics
Data Science

Background:

Understanding soil behavior is crucial for infrastructure development.
Void ratio limits and particle characteristics significantly influence soil properties.
Existing datasets often lack comprehensive data for advanced modeling.

Purpose of the Study:

To compile a detailed database of soil properties for geotechnical analysis.
To consolidate data on void ratios, particle size, distribution, and shape.
To facilitate the development of probability-based void ratio predictive models.

Main Methods:

Compilation of data on minimum and maximum void ratios (e_min, e_max), their range (e_max-e_min), particle roundness (R), sphericity (S), fines content (FC), coefficient of uniformity (C_u), and mean grain size (D_50).
Inclusion of data from natural cohesionless soils and reconstituted materials like rice, glass beads, and mica.
Soil classification using the Unified Soil Classification System (USCS), with ASTM D2487-17 standards applied for missing classifications.

Main Results:

A dataset of 636 soil samples was created, with varying data availability for different parameters (e.g., e_max, e_min, D_50, C_u, R, S, FC).
The dataset includes a diverse range of soils: 19 silts and clays, 527 sands, and 47 gravels.
A spreadsheet summary of the dataset is provided for accessibility.

Conclusions:

The compiled dataset provides a valuable resource for geotechnical research.
The data is foundational for developing advanced, probability-based models to predict soil void ratios.
This work enhances the understanding of soil characteristics and their impact on engineering applications.