Pullout Capacity of Strip Anchors in Spatially Variable Soil. I: Clay
Bibliographic record
Abstract
Natural soils often exhibit significant spatial variability due to their geological history of soil formation. As an attractive anchoring solution for floating offshore structures, this paper has investigated the pullout capacity of strip plate anchors in clay considering the inherent soil spatial variability. In this study, the soil properties were represented by random fields, and an analytical framework was developed to estimate the first two moments and the probability density function of the pullout capacity factor for shallowly and deeply embedded anchors. The analytical approach was validated by the random finite element method (RFEM) over a wide range of soil and anchor parameters. The results show that the coefficient of variation and correlation length of the soil significantly affect the prediction of anchor pullout capacity, providing evidence that sufficient site investigation is of great importance for cost-effective and reliable anchor design. Probabilistic charts were also developed to aid in the probabilistic analysis of anchor pullout capacity. Overall, the developed analytical framework can be used as a good approximation to the computationally intensive RFEM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".