Paste, aggregate, or air? That is the question

  • 0Department of Civil & Mineral Engineering, University of Toronto, Toronto, Ontario, Canada.

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Summary

This summary is machine-generated.

The Gordie Howe International Bridge uses advanced automated methods to assess air entrainment in concrete, ensuring durability. This study demonstrates a new neural network approach for automated paste content determination in large-scale infrastructure projects.

Area Of Science

  • Civil Engineering
  • Materials Science
  • Construction Technology

Background

  • The Gordie Howe International Bridge, a significant North American infrastructure project, requires durable concrete for its harsh environment.
  • Traditional methods for assessing concrete quality, like air entrainment, can be time-consuming and labor-intensive.

Purpose Of The Study

  • To detail the application of ASTM C 457 Procedure C, Contrast Enhanced Method for air void assessment in the Gordie Howe International Bridge project.
  • To demonstrate a novel approach for automated paste content determination using recorded data from manual point counts and neural network training.

Main Methods

  • Utilized the ASTM C 457 Procedure C, Contrast Enhanced Method for automated microscopic analysis of air voids in hardened concrete.
  • Employed digital image processing for air void characteristic determination.
  • Recorded digital image coordinates and phase identifications during manual point counts to train a neural network for automated paste content analysis.

Main Results

  • Successfully applied automated air void assessment on a large scale for North American infrastructure.
  • Demonstrated the feasibility of training a neural network for automated paste content determination, complementing traditional methods.
  • Ensured the quality of air entrainment in concrete crucial for the bridge's durability in a freeze-thaw environment.

Conclusions

  • The automated microscopic approach for air void assessment, as per ASTM C 457 Procedure C, is effective for large-scale infrastructure.
  • The developed neural network offers a promising method for automated paste content determination, enhancing quality control in concrete construction.
  • This integrated approach ensures the long-term durability of critical infrastructure like the Gordie Howe International Bridge.

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