Impacts of anisotropy and exposure conditions on ASR-induced deterioration in columns from the Robert-Bourassa/Charest overpass after nearly 50 years of service
Bibliographic record
Abstract
The anisotropic behaviour of 50-year-old reinforced concrete bridge columns affected by alkali–silica reaction (ASR) was investigated, focusing on the Y-shaped columns of the Robert-Bourassa/Charest overpass in Québec, Canada under different exposure conditions. A multi-level assessment approach, incorporating microscopic and mechanical evaluations, was employed to evaluate ASR-induced damage, with an emphasis on anisotropic expansion, stress redistribution, mechanical property degradation and cracking orientations. Diagnostic tools such as the stiffness damage test and damage rating index provided insights into internal microcracking and reduction of the modulus of elasticity, accounting for the influence of environmental exposure conditions. Measurements of strain and residual tensile strength from reinforcement stirrups further revealed the structural implications of ASR anisotropic progression, including reinforcement embrittlement and loss of confinement. The findings highlight the critical role of exposure conditions, reinforcement configuration, and geometric constraints in shaping the deterioration patterns of ASR-affected concrete.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".