Application of UWB Arrays for Material Identification of Multilayer Media in Metallic Tanks
Bibliographic record
Abstract
In this paper, a compact eight-element antenna array is designed for ultra-wide band (UWB) pulsed radar in highly reflective metallic environments, such as storage and transport tankers. The impact of the sidewalls in metallic tanks is to increase noise and create spurious signals due to sidewall reflection that limits accuracy and causes liquid level and material property measurement errors. The designed Vivaldi antenna and array are characterized in terms of the transient energy patterns and the signal fidelity given in terms of the off-angle signal correlation. Comparison with horn antennas is made. Antenna transient signals are calculated from the frequency-domain data. The 10-dB transient energy pattern beamwidth in the E-plane is improved from 130° to 50° using the eight-element array versus single element. Also, the signal correlation and fidelity for off-broadside angles is greatly reduced. The reflection data from a multilayer of canola oil on metal-backed marble is processed with a calibrated layer-stripping technique for material properties. The transient radiation patterns of the array are compared to that of two horn antennas with similar dimensions. The noise/interference and measurement error is shown to be greatly reduced using an array compared to horn antennas in a realistic tank environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".