Analysis of the Impact of Flow on the Underwater Acoustic Channel
Bibliographic record
Abstract
Reliable and power efficient underwater communication systems that can adapt to the mediums changing nature can be designed with knowledge of the physical underwater environment This paper discusses a stochastic model for an underwater acoustic channel that takes into consideration the effects of flow and turbulence on the acoustic signal in environments subject to some of the highest tides in the world. The model that relies fundamentally on ray tracing generates an ensemble of time-varying channel characteristics by capturing the effect of known environmental changes including changes in sound speed due to mean and turbulent flow. The model is used to extract the channel characteristics such as channel gain, delay spread, Doppler spread, and the arrival time of the signal. By validating simulation results with real measurements taken in the Bay of Fundy, it is demonstrated that the mean flow has significant impact on various channel characteristics. In fact, flow causes large variance on the path that is subject to a surface bounce. This effectively induces a channel that has amplitude variation and delay spread variation, as a function of tide height.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".