Stability of bubbles in a linear elastic medium: Implications for bubble growth in marine sediments
Bibliographic record
Abstract
Methane bubbles in muddy fine‐grained sediments grow initially through a process of elastic expansion, punctuated by discrete fracture events (LEFM‐growth). The ability of the surrounding sediments to support a stress and actively resist expansion can, under conditions of low gas production or high sediment toughness, result in the cessation of growth and the presence of stable bubbles. Thus, it is possible for a bubble to stop growing despite the presence of a source in the sediments that continues to produce gas. This contrasts with growth of bubbles in a fluid medium, which cannot support a stress and so will continue to grow as long as a surrounding source provides gas. This “no‐growth” condition is the result of the coupling between gas supply (methane production or supersaturation) and the sediment mechanics. Here we quantify this condition and present a criterion for the switch between no‐growth and the LEFM growth regimes. We apply this theory to the sediments of Eckernförde Bay, in the Kiel Bight, Germany, and despite the absence of measurements for the key sediment mechanical properties, we can provide a qualitative explanation for the sizes and shapes of the observed bubble population with depth in the sediment. We also show how the release of hydrostatic pressure can stimulate growth, by pushing otherwise stable bubbles into the LEFM growth regime. This could provide a mechanism for the release of bubbles during periods of low water, such as during low tide or wave events.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".