Displacement-based design procedure for slope-stabilizing piles
Bibliographic record
Abstract
Vertical piles are widely employed around the world to prevent landslides, and they are commonly designed with the aim of reducing the soil displacement rate well before the activation of the potential failure mechanism. The design strategies usually adopted in engineering practice are often based on oversimplified approaches, not taking into account any realistic interaction mechanism between pile and soil, and they are not suitable for predicting the effectiveness of the mitigation structure in terms of reduction in the soil displacement rate. This paper attempts to address the problem by proposing a simplified displacement-based numerical procedure, providing engineers with a simple, physically based and easy-to-run tool, particularly useful in pre-dimensioning phases for the system. The importance of a correct description of the soil–pile mechanical interaction and even of possible nonlinearities in pile behaviour is quantitatively discussed by means of numerical analyses based on simplified geometries, proving that the soil–structure interaction forces cannot a priori be foreseen, but that their evaluation requires a displacement-based procedure. The proposed approach appears to be very useful even for prediction of the long-term behaviour of the system. This framework allows the capture of even the remarkable influence that the shape of the soil displacement profile has on the mechanical response of the system, thus implying that a reliable on-site monitoring system is necessary for the optimum design of the structure.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".