Large strain consolidation model for very soft soils with prefabricated horizontal drains considering nonlinear compression and creep
Bibliographic record
Abstract
Abstract The use of horizontal drains assisted by vacuum loading is an effective method for speeding up the consolidation of dredged soil slurry. However, few studies developed models for the large strain consolidation of clayey slurry with prefabricated horizontal drains (PHDs) under self-weight and vacuum loading considering the effects of nonlinear compression and creep. This study introduces a PHD-assisted finite strain consolidation model considering nonlinear compression and limited creep by incorporating an improved elasto-viscoplastic constitutive equation. Firstly, the governing equations for the consolidation of very soft soil with PHDs were derived and solved by the finite-difference method. Subsequently, the proposed consolidation model was verified by comparing the calculations with the finite element solutions, a laboratory model test, and a field trial performed in Hong Kong. Good agreement with the numerical solutions and measured results indicates that the proposed model can capture the consolidation features with PHD combining staged filling and time-dependent vacuum loading. Then, the proposed model was used to estimate a self-weight consolidation test and field test in Japan to show the performance of the proposed model. Finally, parametric studies were conducted to explore the influence of nonlinear compression and creep on the consolidation of soft soil with PHDs.
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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 | 0.000 |
| 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".