研究目的
To numerically apply the passive thermal infrared method for detecting defects in tunnel concrete linings, investigate heat transfer mechanisms, and determine the influence of cavity type, temperature differences, and void depth on detection accuracy.
研究成果
The numerical model effectively simulates heat transfer in defected tunnel linings, showing that a temperature difference greater than 0.35 °C between concrete surface and tunnel air is ideal for detecting voids up to 30 mm deep. Closed cavities are easier to detect than open ones. Future work should include field data on temperature variations with height and investigate cavities with different alignments.
研究不足
The study is limited to numerical simulations and specific field data; actual environmental variations and material inhomogeneities may affect accuracy. The radiation effect on voids is ignored in the model for better agreement with measurements, which may not capture all real-world scenarios. Void depths are assumed up to 50 mm, and the model does not account for cavities with different alignment angles.
1：Experimental Design and Method Selection:
The study uses numerical modeling to simulate heat transfer in concrete, tunnel air, and air inside voids, considering conduction, convection, and radiation mechanisms. The model is validated by comparing with field thermal data measurements.
2：Sample Selection and Data Sources:
Field thermal data from an RC box-type tunnel and a shield tunnel with RC lining are used, including temperature measurements of tunnel air, healthy concrete surfaces, and unhealthy concrete surfaces over 24-hour periods.
3：List of Experimental Equipment and Materials:
A thermal camera for infrared thermography, hammering test equipment for void detection, and numerical analysis software (Midas NFX) are employed. Materials include concrete segments with specified thermal properties and air.
4：Experimental Procedures and Operational Workflow:
Field measurements are conducted during train non-operating hours. Numerical analyses involve modeling a concrete block with a cavity, setting initial temperatures based on field data, and simulating heat transfer over time. Parameters such as void depth and type (open or closed) are varied.
5：Data Analysis Methods:
Temperature differences between healthy and unhealthy surfaces and between concrete surface and tunnel air are analyzed. The void detection ratio is calculated by comparing IRT results with hammering test results. Numerical results are fitted to field data to validate the model.
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