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Record W4412992071 · doi:10.1139/cjce-2024-0407

Fracture damage and softening constitutive relationship of polyethylene fiber-reinforced composite concrete under freeze–thaw cycles

2025· article· en· W4412992071 on OpenAlexvenueno aff
Qingfeng Chen, Ang Wang, Jingmin Duan, Weizhun Jin, Min Huang, Dashuai Chen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComposite numberComposite materialSofteningFracture (geology)FiberPolyethyleneConstitutive equationFiber-reinforced concreteStructural engineeringFinite element methodEngineering

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.207
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicInnovative concrete reinforcement materialsFrench-language works237,207