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The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees

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Moisture Distribution and Ice Front Identification in Freezing Soil Using an Optimized Circular Capacitance Sensor.

Xing Hu¹, Qiao Dong¹, Bin Shi¹

¹Department of Roadway Engineering, Southeast University, Nanjing 211189, China.

Sensors (Basel, Switzerland)

|November 27, 2024

Summary

A novel mobile circular capacitance sensor (MCCS) accurately visualizes the ice front in frozen soil. This non-invasive method precisely maps moisture distribution and ice front positions, crucial for safe geotechnical engineering.

Keywords:

electrical capacitance tomography frozen soil ice front moisture distribution three-dimensional reconstruction

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In Situ Soil Moisture Sensors in Undisturbed Soils

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

Area of Science:

Geotechnical Engineering
Geophysics
Material Science

Background:

The ice front in frozen soil presents abrupt mechanical property changes, posing risks to engineering projects.
Accurate ice front localization is critical for safety and efficiency in frozen soil engineering.
Electrical Capacitance Tomography (ECT) offers a non-invasive, cost-effective solution for frozen soil visualization.

Purpose of the Study:

To design and optimize a mobile circular capacitance sensor (MCCS) for frozen soil analysis.
To evaluate the MCCS's capability in determining moisture distribution and ice front position.
To validate MCCS performance through comparison with simulation results.

Main Methods:

Fuzzy optimization design utilizing multi-criteria orthogonal experiments for sensor development.
Measurement of frozen soil samples along depth to obtain moisture distribution.
3D image reconstruction for precise ice front visualization.
Comparison of experimental data with COMSOL Multiphysics simulation results.

Main Results:

The optimized MCCS meets diverse performance requirements.
Average permittivity distribution effectively reflects moisture distribution with good correlation.
3D reconstructed images accurately pinpoint the ice front location.
Simulations show a low deviation margin for MCCS in ice front identification.

Conclusions:

The MCCS is a viable tool for non-invasively visualizing the ice front in frozen soil.
The developed sensor provides accurate moisture distribution and precise ice front localization.
The MCCS demonstrates potential for enhancing safety and efficiency in frozen soil engineering applications.