Polarization Insensitive X-Band Frequency Selective Surface Sensor for Wireless Thin-Ice Monitoring
Bibliographic record
Abstract
Winter ice conditions present major challenges, particularly for cable-supported bridges where ice accumulates on cables, followed by sudden shedding, creating serious hazards for vehicles and pedestrians. This paper presents a passive and flexible frequency selective surface (FSS) ice sensor designed for wireless detection of thin ice layers over large areas. The proposed FSS fabricated on a 0.1 mm thick substrate, comprises an array of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$6 \times 10$</tex> square-shaped unit cells. A horn antenna was used to interrogate the sensor and measure its <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S_{11}$</tex> response, with the design resonant frequency set at 9.38 GHz. Measurement results demonstrated that the microwave FSS sensor achieved a sensitivity of approximately 260 MHz for a 5 mL ice layer covering its surface, highlighting its potential for effective ice monitoring to enhance the safety of cable-supported bridges. Additionally, the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S_{11}$</tex> results showed distinct responses for ice thicknesses up to 3 mm, confirming the sensor's capability to differentiate ice thicknesses within this range.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".