Design for the improvement of soils with liquefaction potential using Rammed Aggregated Piers
Bibliographic record
Abstract
This paper presents the use of Rammed Aggregated Piers (RAP) for soil improvement; this implementation gives the soil a greater load capacity and provides settlements lower than the admissible.In addition, it mitigates the liquefaction phenomenon in loose sands.The present project is an analytical study where calculations were made considering the construction of a building implementing soil improvement with RAP, which, in first instance, the settlements in the unimproved ground were evaluated using the methodology of Idriss & Boulanger (2008) considering the correction factor for depths of Cetin et al. (2009).Subsequently, the RAPs were implemented and the settlements in the improved soil were evaluated following the 3-step methodology proposed by Geopier.The implementation of the RAP presented a significant improvement in different aspects such as settlement, which was observed that in the results of the settlement calculations all the analyses were less than the admissible settlement (1inch).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".