Restrained Shrinkage of High-Performance Ready-Mix Concrete Reinforced with Low Volume Fraction of Hybrid Fibers
Bibliographic record
Abstract
Cracking due to restrained shrinkage is a recurring issue with concrete bridge decks, impacting durability and ultimately service life. Several scholars' research has proven that the incorporation of fibers in concrete mitigates restrained shrinkage cracking when utilizing high (0.5-3%) fiber volumes. This often presents a mixing and placement issue when used for ready-mixed concretes, which discourages their use in bridge decks. This study aims to optimize the incorporation of fibers for their benefits while producing concrete that is conducive to ready-mix, jobsite use. A series of tests were performed on a high-performance concrete (HPC) mix which incorporated blended, multiple fiber types (steel crimped, macro polypropylene, and micro polypropylene) while maintaining low total fiber (0.19-0.37%) volume. These "hybrid" fiber mixes were tested for multiple mechanical properties and durability aspects, with a focus on the AASHTO T334 ring test, to evaluate fiber efficiency under restrained conditions. Promising results indicate the use of a low-volume hybrid fiber addition, incorporating a macro and micro polypropylene fiber (0.35% by volume) blend, reduced the cracking area by 16.6% when compared to HPC incorporating a single fiber type, and 39% when compared to nonfibrous HPC control mixture.
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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 | 0.000 |
| 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".