SwathDop: Multibeam Pulse-Coherent Doppler Sonar for Scanning 2D Velocity Sections near the Sediment–Water Interface
Bibliographic record
Abstract
Abstract This paper considers the problem of accurately measuring the sediment transport over bedforms where flow evolves continuously both in time and space. For this purpose, we have developed a pulse-to-pulse coherent Doppler sonar system designed in bistatic geometry with two fan-beam transmitters symmetrically positioned on each side of a multielement receive array. The system resolves 2D velocity components within a ±20° (~0.5 m by ~0.5 m) swath. The software-defined radio data acquisition and control system limited us at present to eight independent receiver channels, and consequently the azimuthal resolution of the system is 4°. As a preliminary test of the sonar system, the system operation was simulated using a model developed to predict coherent sonar performance. The uncertainties with respect to the prescribed values and mean measurements in the model results were confined to 0.35 and 0.23 cm s −1 , respectively, in the presence of strong shear (~150 s −1 ) and 50 cm s −1 horizontal flow. An important thing is that the model allowed us to test and develop the signal processing algorithms necessary to invert the multibeam sonar data. Using sand of 0.4-mm median diameter, the laboratory trials were carried out in active sediment transport conditions over dunes with 2-m wavelength and ~0.90 m s −1 unidirectional flow velocities. The results presented here focus mainly on 2D velocity field and indicate an average 4% deviation from the wake law and 8% from independent observations made with the wide-band multifrequency coherent Doppler profiler (MFDop) instrument under similar flow conditions.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".