STRENGTHENING UNDERGROUND REINFORCED CONCRETE STRUCTURES USING EXTERNALLY BONDED CARBON FIBRE-REINFORCED POLYMER SHEETS
Bibliographic record
Abstract
Globally, most of our infrastructures have deteriorated or reached the end of their intended lifespan due to changes in usage or structural degradation. As a consequence, they are in urgent need of repair, strengthening, rehabilitation, or replacement. Canada is no exception and is facing challenges due to the condition of its concrete infrastructure, which requires immediate attention. For instance, the underground core network in Calgary's downtown, which comprises approximately 2735 manholes and 476 transformer vaults, exhibits severe deterioration. While replacing these underground structures with new ones would be ideal; however, it is not an option as it is often financially and operationally impractical due to their location and continuing usage. Therefore, repairing and strengthening these structures using Externally Bonded Carbon Fibre Reinforced Polymer (EB-CFRP) sheets is crucial for the safety of Calgarians. Hence, this paper aims to investigate the feasibility and effectiveness of using EB-CFRP sheets to restore the original flexural capacity of these deteriorated structures.
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 | 0.000 | 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 | 0.001 |
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".