Laboratory experiments with an FM-CW reflectometry system proposed for detecting and monitoring bridge scour in real time
Bibliographic record
Abstract
Thousands of bridges throughout the United States have been identified as being scour critical (i.e., susceptible to failure from pier and (or) abutment scour). Scour occurs during times of rapid river flow when sediments, including rocks, gravel, and silt, are transported by the currents, undermining bridge pier foundations and similar structures. It can be increased by the presence of an ice cover. The scour process is dynamic; erosion and deposition can occur during the same high-energy river event, so the worst-case and the net effect cannot be easily predicted or dynamically monitored using previously available equipment. Herein, a technique and system (U.S. Patent #5,790,471) employing frequency modulated - continuous wave (FM-CW) reflectometry are discussed. This system is proposed for continuous monitoring of the extent of scour around riverine structures. A bench scale version of the system with a 490-MHz linearly swept bandwidth was implemented and tested in the laboratory, where sediments were incrementally added to a water-filled plastic barrel containing an 86-cm-long scour probe. Reflectometer data were taken after each increment of sediment was added. The data indicating the sediment boundary were plotted in a waterfall format that clearly shows the progressive sedimentation. This system has the potential for continuous round-the-clock operation and accuracy to within 5 cm of sediment depth. Key words: reflectometry, real-time monitoring, frequency modulated continuous wave, scour, sediment transport.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".