Effect of Gravel Content on Mechanical Performance and Porous Structure of Concrete
Bibliographic record
Abstract
Concrete is the most widely used material in the field of civil engineering. In order to obtain a strong and durable concrete, it is necessary to study the various parameters entering into its formulation. Mainly the elements forming the concrete skeleton, in particular the gravel content. The transfer of water into concrete directly affects its durability. This transfer is linked to the porous structure and to the continuity of the pores in the concrete. This research studies the effect of gravel content on compressive strength, porosity accessible to water, depth of water penetration and ultrasonic velocity of concrete samples. The study includes 15 types of concrete made by varying the gravel-sand ratio (G/S), 0, 1, 1.5, 2 and 2.5. The cement dosage is taken equal to 150, 250 and 350 Kg/m3. The tests are carried out on cubic samples 10x10x10 cm3 and 15x15x15 cm3 after storage in water for 28 days. The experimental results obtained show that the gravel-sand ratio (G/S) affects the mechanical strength and the porous structure of concrete. Increasing the gravel content in concrete leads to an increase in mechanical strength and ultrasonic speed. However, a high gravel content results in a reduction in the porosity accessible to water and the depth of water penetration.
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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 | 0.001 |
| 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".