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Related Concept Videos

Design Example: Joints in Concrete Pavements01:28

Design Example: Joints in Concrete Pavements

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Concrete pavement joints are essential for maintaining the structural integrity and longevity of pavement by controlling where and how the pavement cracks. These joints can be categorized based on their functions, such as contraction or control joints, construction joints, isolation joints, and expansion joints.
Contraction joints are typically formed by sawing a groove into the concrete shortly after it has hardened. This creates a weakened vertical plane, deliberately encouraging cracking at...
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Masonry in Cold and Hot Weather Conditions01:21

Masonry in Cold and Hot Weather Conditions

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In cold weather, masonry construction requires specific precautions to ensure mortar does not freeze before curing, as this can significantly weaken its strength and watertightness. Mortar temperature should be maintained between 60°F and 80°F to support proper hydration and curing. Below 40°F, mortar water must be heated, but should not exceed 120°F as high temperatures can reduce mortar's compressive and bond strength.
Other key practices include keeping masonry units...
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Cold Weather Concreting01:27

Cold Weather Concreting

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When freshly poured concrete is exposed to freezing temperatures before it has set, the water within the concrete can freeze. This expansion disrupts the setting process, delays chemical reactions necessary for hardening, and increases the volume of pores within the hardened concrete, which weakens its overall structure. If the concrete manages to reach an appreciable strength before it freezes, the damage can be somewhat mitigated.
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Frost Action on Concrete01:27

Frost Action on Concrete

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Concrete structures in cold climates, such as those along roadsides, can retain moisture. This moisture makes them susceptible to frost-related damage when temperatures fall below freezing. Adding moisture worsens the damage during temperature fluctuations, leading to repeated freezing and thawing. De-icing salts, spread over these structures to melt ice, add to the freeze-thaw cycle, and draw even more moisture into the concrete.
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Frost Resistant Concrete01:29

Frost Resistant Concrete

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Concrete's susceptibility to frost damage during freeze-thaw cycles demands strategic measures to enhance its frost resistance. Employing techniques like air entrainment, adjusting the water-cement ratio, proper curing, and selecting appropriate aggregates are essential.
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Precipitation Gravimetry01:03

Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
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RETRACTED: Ndaguba et al. Operability of Smart Spaces in Urban Environments: A Systematic Review on Enhancing Functionality and User Experience. <i>Sensors</i> 2023, <i>23</i>, 6938.

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Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall
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Evidential Data Fusion for Characterization of Pavement Surface Conditions during Winter Using a Multi-Sensor

Issiaka Diaby1, Mickaël Germain1, Kalifa Goïta1

  • 1Centre d'Applications et de Recherches en Télédétection (CARTEL), Département de Géomatique Appliquée, Université de Sherbrooke, Québec, QC J1K2R1, Canada.

Sensors (Basel, Switzerland)
|December 28, 2021
PubMed
Summary

This study introduces a novel road weather analysis method using combined camera and microphone data. This approach enhances the prediction of dangerous road conditions, particularly during winter, by analyzing pavement states in real-time.

Keywords:
data fusiondeep learningintelligent systemsmulti-sensor systemspavement surface conditions

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Area of Science:

  • Road Weather Analysis
  • Sensor Fusion
  • Deep Learning

Background:

  • Accurate road weather analysis is crucial for traffic safety, especially during winter.
  • Real-time pavement condition monitoring is essential for anticipating hazardous driving environments.
  • Existing methods may lack comprehensive real-time data for effective road condition assessment.

Purpose of the Study:

  • To propose a new data acquisition approach for road weather analysis.
  • To characterize pavement conditions using a combination of visual and auditory sensor data.
  • To explore the efficacy of evidential theory for data fusion in deep learning models for road surface analysis.

Main Methods:

  • Real-time data acquisition using a camera for road imagery and a microphone for tire-pavement acoustics.
  • Application of distinct deep learning architectures for analyzing data from each sensor.
  • Evidential theory-based data fusion to combine sensor outputs for improved surface state classification.

Main Results:

  • Demonstrated a proof of concept for an evidential approach to enhance deep learning classification accuracy.
  • Successfully characterized road surface conditions by combining visual and acoustic sensor data.
  • Validated the potential of low-cost sensors for real-time road weather analysis.

Conclusions:

  • The proposed sensor fusion method shows promise for improving road condition classification accuracy.
  • Evidential theory provides a robust framework for combining data from multiple sensors in road weather analysis.
  • The approach is scalable, with potential for integrating more sensors and networked nanocomputers for broader urban environment analysis.