The Microscopic Failure Mechanism of Hydrate-Bearing Sand Under Direct Shear: Insights from 3D DEM Simulation
Bibliographic record
Abstract
Gas production in hydrate reservoirs can lead to large deformations, causing wellbore or platform instability, reservoir subsidence, and submarine landslides. However, current research on the mechanical responses of hydrate reservoirs under large deformations is not thorough. Benefiting from direct shear tests on hydrate-bearing sands, this study employed the discrete element method to conduct further microstructure characterizations and failure mechanism analysis on calibrated numerical specimens. The results indicate that specimens’ responses under shear loading can be generally divided into elastic, yielding, strain-softening, and residual-deformation stages, where specimens with higher hydrate saturation exhibited higher peak and residual strengths, larger volumetric dilation, more bond breakage, and a larger coordination number. The local stress concentration and dominant force chains evidently formed and developed during the yielding and strain-softening stages, and the shear bands were clearly observed by distinct particle translations and rotations around the shear surface. The widths and angles of the shear bands decreased with increasing hydrate saturations because of the concentrated strong force chains. The local porosity within the shear band increased with a large shear displacement and higher hydrate saturation, contributing to the macro dilation of the specimen. A tensile-dominated failure mode of the specimens during shear loading was observed, and parts of the tensile failure may gradually transform into shear failure with increasing hydrate saturation, due to particle cluster rotation suppressed by the hydrates. These findings provide microscopic mechanical insights for hydrate reservoirs under large shear deformations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".