Compaction, strength, and volume change characteristics of excavated clayey soil stabilized with composite admixture of cement and autoclaved aerated concrete powder
Bibliographic record
Abstract
Low-strength and highly compressible excavated clayey soils are common in geotechnical engineering, which cannot serve as a bearing stratum and typically end up being disposed of in landfills. Autoclaved aerated concrete powder (AACP) is a lightweight and porous waste material, with its stockpiles rapidly accumulating worldwide. To promote sustainable development in geotechnical engineering, a type of composite admixture consisting of cement and AACP was developed to modify clayey soils in this study. The physical and mechanical properties of untreated and the composite admixture-treated soil samples were investigated via Atterberg limits, compaction, bender element, constraint compression, free swell, and unconfined compressive strength (UCS) tests. The physicochemical and microstructural observations, including soil pH, scanning electron microscopy, and mercury intrusion porosimetry analyses, were conducted to interpret the macroscopic mechanical behaviors. Test results showed that the incorporation of AACP improved the workability of clayey soils, while cement further enhanced their mechanical properties. Hydration compounds primarily filled the voids with a diameter ranging from 0.1 to 1 µm. From the perspective of volume change behavior, 8% cement content was recommended. Shear wave velocity showed a strong correlation with the UCS, demonstrating that the bender element technique was an effective non-destructive tool for assessing the strength of compacted samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".