Off‐axis compression behavior and failure mechanisms of needled carbon/quartz fiber reinforced phenolic resin composite based on acoustic emission
Bibliographic record
Abstract
Abstract The effect of the off‐axis angle (note as θ) on compressive properties and failure mechanisms in needled carbon/quartz fiber reinforced phenolic resin (CF‐QF/PF) composite has been investigated. For this objective, a series of quasi‐static off‐axis compression tests were performed, and a more precise and general model for predicting the compressive modulus and strength has been proposed. Further, the acoustic emission (AE) technology, including parameter‐based analysis and the Hilbert Huang Transform (HHT) method, was also employed to scrutinize the intricate damage mechanisms. The results show that specimens with θ = 0° exhibit linear and brittle behavior and are the most dangerous scenarios because delamination (accounting for 58% of the total AE accumulative energy) dominates their failure. For specimens with small off‐axis angles (0° < θ ≤ 45°), the fiber‐matrix interface determines their compressive properties. While for specimens with large off‐axis angles(45° < θ ≤ 90°), the enhanced transverse load‐bearing capacity of fibers becomes the dominant factor, characterized by significant debonding (33% when θ = 60°) and fiber breakage (27% when θ = 90°). Finally, these results were verified by optical microscopy (OM) and scanning electron microscopy images (SEM). Highlights Off‐axis compression behaviors of needled CF‐QF/PF composite are studied. A more precise and general model for predicting off‐axis compression properties is proposed. Acoustic emission technology is used to quantify different types of damage. Failure mechanisms are revealed by combining in‐situ and offline techniques.
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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".