Nearshore Migration of Munitions and Canonical Objects Under Large-Scale Laboratory Forcing
Bibliographic record
Abstract
A quantitative understanding of the migration of munitions and canonical objects in the nearshore is needed for the effective management of contaminated sites. Migrations of munitions with a density range of 2000 kg/m3 to 5720 kg/m3 were quantified in a large-scale wave flume. The forcing consisted of six cases of varying wave heights, periods, still water depths, and durations. The cross-shore profile, typical of natural sandy beaches, was sub-divided into swash, surf, and offshore zones. Overall, 2228 migration measurements were recorded with 16% and 84% of the migration observations classified as “motion” (net distance > 0.5 m) and “no motion” (net distance ≤ 0.5 m), respectively. The probability of munitions migration increased with proximity to the shoreline. There was a nearly equal probability of onshore or offshore migration in the swash zone. Migration in the surf zone tended to be offshore-directed (65%), while migration was onshore-dominant (65%) in the offshore zone. Migration in the offshore zone was preferentially onshore due to skewed waves over flat bathymetry. Less dense munitions in the offshore zone may have migrated offshore likely still related to the skewed nature of the wave profile causing transport in both directions through the majority of the wave phase. The largest migration distances occurred in the surf zone likely due to downslope gravity. Migration in the surf and swash zones is a balance between skewed/asymmetric forcing and downslope gravity, with downslope gravity tending to be pronounced provided the forcing is sufficient to initiate motion. An exception was sometimes observed in the swash zone where onshore forcing was sufficient to transport munitions to the seaward side of the berm where they became trapped in a bathymetric depression between the dune and berm. Relating overall migration (Lagrangian) to fixed hydrodynamic measurements (Eulerian) was ineffective. Parameters such as the Shields number, wave skewness, and wave asymmetry estimated from the closest measurement location were insufficient to predict migration. Large scatter in the migration data resulting from competing hydrodynamic, morphodynamic, and munitions response processes makes robust deterministic predictions with flow statistics and dimensionless numbers difficult.
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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 | 0.001 |
| 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".