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Related Concept Videos

Abrasion Resistance of Concrete01:23

Abrasion Resistance of Concrete

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Abrasion resistance is an essential characteristic of concrete that determines its durability and longevity under various wear conditions. Concrete surfaces are vulnerable to different types of abrasion. For instance, surfaces may wear down due to the constant movement of vehicles or be eroded by solids carried in water, as seen in concrete canal linings. Specific tests are conducted to measure the abrasion resistance of concrete.
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Behavior of Concrete Under Compressive Load01:23

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Concrete exhibits specific behaviors under different compressive loads. Understanding this is crucial for understanding its structural integrity. When concrete undergoes uniaxial compression, it tends to develop cracks that run parallel to the direction of the force. These parallel cracks stem from localized tensile stresses that occur perpendicular to the compression direction. Additionally, angled cracks may appear due to the formation of shear planes.
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Upon subjecting concrete to moderate or high uniaxial compressive or tensile stresses, the strain response is non-linear relative to the stress applied. As the stress is removed, the resulting stress-strain curve deviates from the original path traced during loading, creating a hysteresis loop, indicative of the concrete's non-linear and non-elastic properties. Typically, a material's modulus of elasticity, which is a measure of the material's stiffness, is inferred from the linear...
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Non-destructive Tests for Concrete Strength01:12

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The rebound hammer test, also known as the Schmidt hammer test, is a non-destructive technique for evaluating the hardness of concrete and, indirectly, the strength of concrete. It operates on the principle that the rebound of a spring-driven mass from a concrete surface correlates to the surface's hardness. The device comprises a mass within a tubular housing, a spring mechanism, and a plunger that strikes the concrete. Upon release, the energy imparted to the mass by the spring causes it...
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Creep in Concrete01:22

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Creep refers to the time-dependent increase in strain under a sustained load, excluding other time-dependent deformations associated with shrinkage, swelling, and thermal expansion in concrete. The primary mechanism behind creep involves the loss of physically adsorbed water from the calcium silicate hydrate within the hydrated cement paste. This process is further exacerbated by concrete's non-linear stress-strain relationship, microcrack development in the interfacial transition zone, and...
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Concrete is a fundamental building material, and understanding its strengths is crucial for construction projects. The relationship between its tensile and compressive strengths is intricate, showing that while these strengths are related, they do not increase at the same rate. Tensile strength's growth is slower and is affected by various factors such as the methods used for testing, the size and shape of the specimen, the texture of the aggregate used, and the moisture content of the...
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Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron.

Yimin Mao1, Zhu Licai2, Li Feng3

  • 1School of Information and Engineering, Shaoguan University, Shaoguan, 512005, Guangdong, China. mymlyc@163.com.

Scientific Reports
|November 27, 2023
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Summary

Artificial intelligence, specifically the Multilayer Perceptron (MLP), accurately predicts travertine compressive strength using point-load index data. This enhances excavation planning and drillability assessments in Azarshahr mining operations.

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Area of Science:

  • Geotechnical Engineering
  • Artificial Intelligence in Mining
  • Rock Mechanics

Background:

  • Azarshahr County's geology is dominated by travertine, leading to extensive open-pit mining.
  • Rock drillability and excavation resistance are critical mining factors linked to compressive strength.
  • Traditional rock strength assessment methods lack precision, hindering reliable excavation planning.

Purpose of the Study:

  • To develop an artificial intelligence model for enhanced prediction of Azarshahr travertine's compressive strength.
  • To utilize the Multilayer Perceptron (MLP) for accurate strength estimation.
  • To improve excavation methodologies and drillability assessments in travertine mining.

Main Methods:

  • Compiled a database of 150 point-load index (Is) tests on Azarshahr travertine.
  • Developed and trained a Multilayer Perceptron (MLP) model using the compiled dataset.
  • Validated model accuracy using Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) metrics.

Main Results:

  • The MLP model achieved high accuracy in predicting axial and diametral compressive strength.
  • R-squared coefficients of 0.975 were obtained for both axial and diametral strength predictions.
  • An overall accuracy of 0.968 (AUC) demonstrates the model's effectiveness.

Conclusions:

  • The MLP-based model accurately predicts travertine compressive strength from point-load index data.
  • This AI approach offers significant improvements over conventional methods for rock strength analysis.
  • The predictive model provides valuable insights for optimizing excavation planning and drillability in Azarshahr travertine mines.