Cyclic response of floating geosynthetic-encased steel slag columns in soft clay
Bibliographic record
Abstract
Geosynthetic-encased stone column (GESC) technology for strengthening soft clay offers significant advantages in terms of cost-effectiveness, environmental sustainability, and engineering applicability. It is widely applied in treating soft foundations for railways, bridges, and embankments. This study evaluates the cyclic response of the geosynthetic-encased steel slag column (GESSC) composite foundation employing three-dimensional nonlinear finite element analysis. A numerical study is conducted to assess the cyclic response of floating GESSC considering the influence of key design variables, including cyclic load amplitude, loading frequency, geosynthetic encasement stiffness, and length-to-diameter ratio. Results show that both cyclic load amplitude and frequency affect the cumulative settlement and excess pore pressure within the GESSC foundation. Within specified limits, increasing the encasement stiffness and column length can significantly improve the GESSC load-bearing characteristics. The parametric study suggests an optimal geosynthetic encasement stiffness for the field prototype columns within the range of 4480–5760 kN/m and a critical steel slag column length of 10 times the column diameter.
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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 | 0.000 | 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".