Relationship Between Particle Shape and Void Content of Fine Aggregate
Bibliographic record
Abstract
Abstract Fine aggregate characteristics have an important influence on water demand and related properties of concrete. Several test methods for measurement of fine aggregate angularity are reported in the literature. These tests typically provide a single number that represents the bulk, or average angularity of the sand. An understanding of the relationship between bulk measures of angularity, individual particle geometry and shape characteristics, and concrete properties is important to aggregate producers, concrete suppliers, consulting engineers, other design professionals, particularly as existing deposits of sand are consumed and alternate sources must be developed. As part of a comprehensive research program on manufactured sand properties and their effects on fresh and hardened concrete properties, an image analysis technique was developed to determine the shape characteristics by photographing and analyzing sets of individual grains of sand. The outlines of the grains were analyzed using a variety of geometrically derived characteristics. The relationship between particle shape characteristics and a common measure of bulk angularity, void content (ASTM C 1252), was then examined. Results of the study indicated that void content was significantly influenced by the presence of deep indentations in the surface of the sand particle and deviations from a cubical particle shape.
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 | 0.002 |
| 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".