Experimental analysis of rolling dynamic compaction using transparent soils and particle image velocimetry
Bibliographic record
Abstract
Rolling dynamic compaction (RDC) is a soil compaction technique, which is capable of improving thick layers of soil at a relatively fast operating speed. The paper presents the results of laboratory experiments conducted on 1:13 scale models of the four-sided, 8 and 12 t, Broons BH-1300 and BH-1300 HD impact rollers, respectively, to study the performance of the scale model at four different operating speeds. A series of laboratory tests is undertaken using transparent soils and the particle image velocimetry (PIV) technique to investigate the effectiveness of the models. The transparent soil employed in this study consists of fused quartz and a pore fluid that matched the refractive index of the fused quartz. A one-particle thick layer of coloured fused quartz is embedded in the centre plane of the transparent soil to visualize soil internal displacements and a digital camera is used to capture the speckled pattern during the scale model testing process. The results show that the heavier module induces greater soil displacements at each operating speed. The optimal operating speed is approximately 299 mm/s for both module weights. The most significant soil displacements occur within the first 20 passes and no obvious ground improvement is observed after 35 passes. The results of this study demonstrate the unique capability of transparent soil to study soil displacements induced by the ground improvement scale models.
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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".