Nonlinear consolidation of soft foundation improved by prefabricated vertical drains based on elliptical cylindrical equivalent model
Bibliographic record
Abstract
Abstract This study builds up an elliptical cylindrical equivalent model (ECEM) of prefabricated vertical drains (PVD)‐improved foundation which incorporates the nonlinear variation of compressibility and permeability and the preconsolidate state of soil. An exact solution and a simplified solution are derived for the nonlinear consolidation model under a combined vacuum and surcharge preloading. Considering the stratification of improved soil and the reduction of vacuum pressure along PVD, a precise settlement prediction method is proposed. The rightness and applicability of present solutions are verified by carrying out a series of comparative analyses. Also, a parametric study is conducted to investigate the characteristics of nonlinear consolidation under different , , over‐consolidation ratios (OCRs). The results show that, when the applied load has no impact on the dissipation of excess pore‐water pressure, whereas a larger applied load would induce a quicker settlement rate; the consolidation rate would be underestimated if the over‐consolidated stress history is neglected, and greater OCR produces more obvious underestimation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".