Semi-analytical approach for time-dependent load–settlement response of a jacked pile in clay strata
Bibliographic record
Abstract
Mechanical behaviour of the soil around a jacked pile changes significantly during pile installation and subsequent consolidation. Hence, an axially loaded jacked pile exhibits apparent time-dependent bearing performance after pile installation. This paper presents a semi-analytical approach to predict the time-dependent bearing performance of an axially loaded jacked pile in saturated clay strata. The effects of pile installation and subsequent consolidation on the changes in mechanical properties of the surrounding soil are modeled by the cavity expansion theory and the radial consolidation theory, respectively. An exponential function–based load-transfer (t–z) curve is employed to describe the nonlinear behaviour of the pile–soil interface during pile loading. The evolutions of the three-dimensional strength and shear modulus of the surrounding soil are subsequently incorporated into the two model parameters of the proposed t–z curve to capture the time-dependent pile–soil interaction behaviour. The time-dependent elastic response of the soil outside the pile–soil interface is also considered in the proposed approach. With the proposed load-transfer curve, an incremental algorithm and a corresponding computational code are developed for assessing the time-dependent load–settlement response of a jacked pile. To verify the proposed semi-analytical approach, predictions of the time-dependent load–settlement curves are compared with the measured values from pile tests at two sites. The good agreement shows that the time-dependent bearing performance can be reasonably predicted by the proposed approach.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".