Effect of polishing time, mechanisms and mineralogy on the microtexture evolution and polishing resistance of pavement surface aggregates
Bibliographic record
Abstract
The LC 21–102 test standard is an accelerated polishing by projection test used in the province of Quebec (Canada), with the objective of theorically bringing pavement surface coarse aggregates to their maximum wear. Their suitability for use in surface layer on high trafficked roads, regarding skid resistance, is then evaluated by measuring their residual friction coefficient using a British pendulum. This study investigates the influence of polishing by projection time, and aims to provide a better understanding of its wear mechanisms by analyzing the evolution of the aggregates microtexture. Four aggregates with different mineralogy and polishing resistance were selected for the study. Their mineralogical, physical and mechanical properties were determined using various techniques, including optical microscopy, X-Ray Diffraction, Los Angeles and Micro-Deval tests. A high-precision 3D laser microprofilometer was used to capture the surface relief of aggregate particles and to determine their microtexture parameters such as peak density, shape and height. A British pendulum was used to measure the residual friction coefficient. Tests were performed prior to polishing and at incremental stages that went beyond the standard time. The results show a continuous decrease in friction values beyond the standard polishing time for all tested aggregates, suggesting the need to extend the polishing time to reach maximum wear. Polishing by projection also appears to operate through a distinct mechanism compared to other well-known methods: it acts more by indentation, digging into the aggregate surface and generating a new microtexture with, on average, less dense but higher and sharper peaks. Furthermore, aggregate type, grain size, general and differential hardness (to a lesser extent) seem to influence the initial microtexture formation and its evolution during polishing. • RHD, DH, and grain size are key factors for initial microtexture and its evolution. • Polishing by projection mechanisms differ from other commonly used methods. • Polishing by projection digs into aggregate surface making peaks taller and sharper. • Polishing aggregates for 20 cycles may overestimate their skid resistance. • Optimal polishing cycle count appears to be around 35 cycles.
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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 | 0.001 | 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 | 0.001 | 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".