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Related Concept Videos

Design Example: Aggregate Gradation01:24

Design Example: Aggregate Gradation

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The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is...
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Maximum Size of Aggregate01:12

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The maximum size of aggregate is defined as the aperture of the sieve retaining 15 percent or more of the particles present in the aggregate sample. The aggregate's maximum size impacts the concrete's water requirement, workability, and strength. Larger aggregates reduce the surface area needing cement paste coverage, which can lower water needs, thereby allowing a decrease in the water-to-cement ratio when the desired workability and richness of the mix are to be maintained, which can...
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Pore Size Distribution01:23

Pore Size Distribution

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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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Aggregate grading is crucial in economically obtaining a concrete mix with adequate strength, reasonable workability, and minimal segregation. There are four types of aggregate gradation: well-graded, uniformly (or one-sized) graded, gap-graded, and open-graded.
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Unsoundness of Aggregate due to Volume Change01:26

Unsoundness of Aggregate due to Volume Change

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Unsoundness in aggregates due to volume changes is primarily caused by the physical alterations aggregates undergo, such as freezing and thawing, thermal changes, and wetting and drying. Unsound aggregates, when subjected to these changes, result in volume change upon disintegration. This, in turn, contributes to the deterioration of concrete, including scaling, pop-outs, and cracking. Particular types of aggregates, such as porous flints, cherts, and those containing clay minerals, are...
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Deleterious Substances in Aggregate01:25

Deleterious Substances in Aggregate

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Deleterious substances in aggregates can be detrimental to the quality and durability of concrete. These substances include organic impurities like loam, which interfere with cement hydration and are usually present in the sand. These prevent a good bond between aggregate and cement paste. Organic impurities can be detected using the colorimetric test, where the darkness of a solution after agitation indicates the level of organic content.
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Statistical Modeling of Near-Surface Aggregate Size Distributions in Concrete.

Alexander Haynack1, Thomas Kränkel1, Christoph Gehlen1

  • 1Centre for Building Materials (CBM), Chair of Materials Science and Testing, Department of Materials Engineering, TUM School of Engineering and Design, Technical University of Munich, 85748 Garching b. Munich, Germany.

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|April 14, 2026
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Summary

This study introduces a computational method to model concrete

Keywords:
aggregate distribution optimizationconcretemesoscale modelingwall effect

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Area of Science:

  • Materials Science
  • Civil Engineering
  • Computational Mechanics

Background:

  • Accurate modeling of concrete mesostructure is crucial for predicting material behavior.
  • Near-surface aggregate distribution significantly influences concrete properties.
  • Existing methods often struggle to efficiently capture wall effects.

Purpose of the Study:

  • To develop a computationally efficient method for estimating near-surface aggregate size distributions in concrete.
  • To optimize the spatial arrangement of aggregates considering formwork boundaries and wall effects.
  • To validate the proposed method against experimental data.

Main Methods:

  • Distribution-optimized mesostructure estimation using Beta distributions for aggregate groups.
  • Minimizing deviation between generated and target cumulative aggregate volume functions.
  • Solving the optimization problem with a derivative-free Powell algorithm.
  • Experimental validation using incremental surface grinding and 3D laser scanning.

Main Results:

  • The optimized mesostructure model accurately predicts measured depth-dependent density profiles.
  • The method inherently captures wall effects, showing smaller aggregates migrating towards boundaries.
  • Higher aggregate volume fractions lead to increased near-surface accumulation of fine particles.
  • Strong agreement between simulated and experimental density profiles was observed.

Conclusions:

  • The proposed method offers a computationally efficient approach for incorporating wall effects into mesoscale concrete models.
  • The technique provides a statistically sound way to model near-surface aggregate distributions.
  • The findings have implications for designing concrete with tailored near-surface properties.