MAT-743: FULL SCALE MANUFACTURING OF STEEL FIBRE REINFORCED CONCRETE PIPE
Bibliographic record
Abstract
A research project titled “Development of Fibre-Reinforced Concrete Pipes” funded by Con Cast Pipe and Natural Sciences and Engineering Research Council of Canada (NSERC) was conducted between 2011 and 2014 by Professor Moncef Nehdi and his research team at Western University to study the structural behaviour of steel fibre reinforced concrete pipe (SFRCP). 142 pieces of SFRCP, and 58 pieces of conventional reinforced concrete pipe (RCP) and non-reinforced concrete pipe with 300 mm, 450 mm, 600 mm inner diameters were manufactured using existing fully-automated equipment. These SFRCP specimens contain various fibre contents and two fibre types. During the manufacturing week, full production and quality crews were deployed to accomplish the planned activities. Over 300 testing cylinders and 60 testing beams were collected. A portion of the pipes were sent to the university for laboratory work and full scale testing. Another portion was tested in the precast plant using conventional testing equipment. This report presents the manufacturing and testing activities in order to demonstrate the practicality of SFRCP manufacturing. The challenges are discussed and concluded at the end of this report providing insights for any future development of SFRCP.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".