Direct and Interface Shear Behavior of an Authigenic Glauconite Sand from the Coastal Plain of New Jersey
Bibliographic record
Abstract
Glauconite sand, a green-colored, iron–potassium micaceous peloid known for its high crushability, has been found at locations in Europe and the United States where offshore wind development is currently underway. Crushing the material increases the fines content and transforms its behavior from sandlike to claylike, which can affect shaft resistance and end bearing during pile driving and long-term axial loading. The strain rate during pile driving can exceed 106% per hour, in which undrained viscous effects dominate the shaft resistance. Following installation, shaft resistance can exhibit a drained or an undrained response, depending on the nature of static and cyclic operational loads and the degree of particle crushing of the soil and its associated drainage properties. Direct shear and interface shear tests were conducted to study the effects of shear rate, interface roughness, and extent of particle crushing on the shear behavior of glauconite sand. Tests were conducted on natural and artificially degraded glauconite sand as well as Ottawa 20-30 sand and Boston Blue Clay to benchmark the results against typical sand and clay behavior. Results show that the peak and residual shear stress decrease as the shear rate increases, transitioning from drained to partially drained conditions. With continued increases in shear rate, viscous effects were observed to increase the shear resistance of degraded glauconite sand. The peak and residual shear stress also decreased with increasing degradation, reaching a minimum after mixing the soil in a dispersion cup for 60 min. The drained peak and residual shear stress between soil and steel followed expected trends related to surface roughness, while roughness effects under undrained conditions were less conclusive. Results are discussed in the context of implications for offshore pile foundation design.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".