Fracture damage and softening constitutive relationship of polyethylene fiber-reinforced composite concrete under freeze–thaw cycles
Bibliographic record
Abstract
To explore the effects of freeze–thaw cycles on polyethylene fiber (PF)-reinforced concrete (PFRC), five sets of specimens with varying PF volume percentages (0%, 0.1%, 0.2%, 0.3%, and 0.4%) were tested. Results indicated that up to 0.3% PF volume, increasing PF content improved crack initiation toughness, unstable toughness, and fracture energy. Beyond 0.3%, these properties slightly decreased. Freeze–thaw damage reduced concrete toughness and energy, but PF mitigated this effect. Higher PF content led to smaller losses in fracture toughness and energy during freeze–thaw cycles. A calculation model for PFRC's freeze–thaw damage was developed from experimental data, and a bilinear softening constitutive relationship curve for PFRC under freeze–thaw conditions was derived based on Petersson's concrete model.
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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 | 0.001 |
| 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 | 0.000 |
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".