Effect of fine particles on strength and stiffness of cement treated sand
Bibliographic record
Abstract
Abstract Naturally available sands are always found with finer particles of varying sizes and proportions which are generally not accounted for in the geotechnical design of a cemented soil system. This paper explores the behavior of cemented sand with fine particles in smaller proportions. Two types of cements: (1) ordinary portland cement (OPC), (2) calcium sulfoaluminate cement (CSA); three cement contents: 3%, 5%, 7% and four fine (kaolin powder) contents: 0%, 1%, 3%, 5% are considered in this study. The ultrasonic pulse velocity (UPV), shear wave velocity ( $$V_{s}$$ Vs ) and unconfined compressive strength (UCS) are measured to investigate the effects of fine particles on the cemented sand. The results show that fine particles do affect quite significantly the mechanical properties of cement-treated sand, even at negligent proportions. The strength and stiffness increase with fine content in both types of cement. The increase in strength and stiffness with increasing fine contents is attributed to the increased density with kaolin acting as a filler material facilitating more contact points among the particles. The results also show that the effect of fine particles on cemented sand depends not only on their relative volume and mineralogy but also on the type of the binding material.
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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".