Analytical estimation of cohesive parameters for a bilinear traction-separation law in DCB mode I loading
Bibliographic record
Abstract
In this study, analytical solutions for estimating two cohesive parameters, stiffness and strength in a bilinear traction law, were developed in conjunction with the ASTM double-cantilever beam (DCB) mode I testing. A zero-thickness elastic foundation zone containing two layers in series was assumed in the analytical derivation: a cohesive zone located underneath a beam elastic zone that is adjacent to the beam bottom surface, for accurately identifying the DCB opening displacements at both loading point and crack tip. The total deflection was comprised of three contributions: bending, lateral shearing, and beam thickness deformation. The analytical analysis eliminates drawbacks caused by rigid thickness in the classical beam theory. Consequently, good agreement in the beam deflections at both the loading point and the crack tip was obtained between the proposed analytical solution and an evaluation of numerical study results. This good agreement ensured that accurate cohesive parameters were derived analytically. Results showed that the proposed method explains why different cohesive parameters can lead to similar load-displacement results. Discussion on the application of the proposed analytical methodology and the associated cohesive values is presented.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".