Combined Puncture and Cutting of Soft-Coated Fabrics by a Pointed Blade: Energy, Force and Stress Failure Criteria
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Bibliographic record
Abstract
Soft elastomer-coated fabrics are widely used in engineering and protective applications. Puncture cutting by sharp-tipped objects is one of the most common failure modes of protective gloves made of coated fabrics. In order to investigate the puncture-cutting process of soft elastomer-coated fabrics, we studied the mechanisms and mechanics of pointed-blade insertion into specimens cut out from four protective gloves. Experimental and analytical analyses showed that total energy and critical puncture-cutting force calculated analytically are both able to predict the puncture-cutting resistance of soft elastomer-coated fabrics measured experimentally. Total energy is obtained from the relationship between the puncture-cutting work and the created fracture area, while critical force is calculated by two analytical models developed for soft elastomeric membranes. The components of the critical puncture-cutting force are predicted analytically and then used to calculate the compressive and shear loading stress components based on the contact surface between the pointed blade tip and material. Since there is a linear relationship between the compressive stress component and shear stress component, a modified linear strength criterion is proposed for puncture cutting of soft elastomer-coated fabrics by a pointed blade. Our stress-based criterion connects the 45° tensile strength (in the 45° direction) and biaxial strengths (in the course direction, 0°, and wale direction, 90°) to both compressive and shear loading stresses. The analytical and experimental results are consistent. This investigation can be used as a guideline to evaluate the puncture cutting of soft elastomer-coated fabrics using an energy-based criterion, critical force-based criterion, or stress-based criterion.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it