Evolution of structure and anisotropic shear stiffness of compacted loess during compression
Bibliographic record
Abstract
Different compaction conditions (water content and density) may induce various soil structures. The influence of these structures on small strain shear stiffness G seems contradictory and is not understood (e.g., denser specimens may have larger or smaller G than looser specimens after compression). Furthermore, the influence of compaction condition on stiffness anisotropy remains unclear. This study investigated the evolution of structure and anisotropic stiffness of saturated and compacted loess during isotropic compression. Specimens compacted at different water contents and densities were explored. The measured G was normalised by a void ratio function ( f ( e)) to eliminate density effects. Before yielding, G/ f ( e) increases with decreasing compaction water content and increasing density. These two trends are reversed at large stresses (2 to 3 times yield stress), implying that an initially softer structure becomes stiffer. Based on mercury intrusion porosimetry, stereomicroscope, and scanning electron microscope results, the trend reversal is likely because interparticle contacts are more strengthened and pores are more compressed in the initially softer specimens. Furthermore, the stiffness anisotropy becomes more significant with decreasing compaction water content and increasing density because of more orientated fabrics, as evidenced by the particle/aggregate directional distribution results.
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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 | 0.001 | 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".