Effects of shear stress path and roughness on shear creep behavior of marine clay-concrete interface
Bibliographic record
Abstract
Floating piles have been widely employed as foundations in coastal regions abounding with marine clay. A growing concern for these floating piles is their long-term performance of bearing capacity. To better understand the time-dependent mechanisms behind the bearing capacity, in this paper a series of shear creep tests was conducted to study the effects of load paths/steps and roughness on shear strain of the marine clay-concrete interface. Four main empirical features were observed from the experimental results. First, the creep process of the marine clay-concrete interface can be largely decomposed into the instantaneous creep stage, the attenuation creep stage and the uniform creep stage. Second, the creep stability time and the shear creep displacement generally increase as the shear stress level increases. Third, the shear displacement rises as the number of loading steps drops under the same shear stress. The fourth feature is that under the shear stress condition, the rougher the interface is, the smaller the shear displacement is. Besides, the load-unloading shear creep tests suggest that: (a) shear creep displacement typically contains both viscoelastic and viscoplastic deformation; and (b) the proportion of unrecoverable plastic deformation increases with increasing shear stress. These tests confirm that the Nishihara model can provide a well-defined description of the shear creep behavior of marine clay-concrete interfaces.
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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 | 0.000 |
| 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 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".