Laboratory development of a vertically oriented penetrometer for shallow seabed characterization
Bibliographic record
Abstract
Current site investigation practice for offshore pipeline design relies on soil parameters gathered from boreholes or in situ test soundings to depths of 1–2 m below the mudline. At these depths, the fine-grained seabed is very soft and possesses low undrained strength, which can be difficult to measure. This paper describes a centrifuge test programme undertaken to evaluate the feasibility and performance of a novel penetrometer designed to assess the shallow strength of soft seabed over continuous horizontal profiles. This device is termed the vertically oriented penetrometer (VOP). Tests were performed on a normally consolidated kaolin sample, with the VOP translated horizontally at velocities ranging from 1 to 30 mm/s, after embedding the VOP at 30 and 45 mm depths. All tests involved many cycles of VOP forward and backward movement to assess its potential to derive the ratio of intact to fully remoulded strength. Strength determination is achieved by dragging the VOP at a specified embedment depth along the soil surface, and deriving the soil strength from the measured resistance as if the VOP were a laterally loaded pile. The VOP is shown to yield comparable strength measurements to that of a T-bar penetrometer. The VOP is a potentially valuable addition to the range of tools used to characterize soil strength, both in small-scale centrifuge models and, following practical development, potentially also in the field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".