Analysis of Fracture Parameters for Compact-Tension-Shear Specimen of Orthotropic Materials
Bibliographic record
Abstract
Abstract Treating orthotropic materials as isotropic for strength analysis and design can introduce significant errors, resulting in considerable safety risks. Furthermore, in practical conditions, cracks often exhibit mixed-mode fracture behavior, and the combination of orthotropy mechanics gives rise to an even more complex stress field in the vicinity. In this context, performing Compact-Tension-Shear (CTS) tests is a promising research methodology to determine fracture toughness of orthotropic materials in mixed mode I&II. Therefore, this study conducted a comprehensive two-dimensional finite element analysis (2D FEA) on orthotropic CTS specimens to assess critical parameters in fracture toughness including stress intensity factors (SIF) and crack mouth opening displacement (CMOD) compliance. The analysis matrix encompassed a wide range of material orthotropy, crack length ratios, and loading angles. Results showed that the impact of orthotropy varies under different geometries and loading angles, while different fracture parameters exhibit varying degrees of sensitivity to orthotropy. The obtained results would contribute to the development of fracture toughness testing methods for orthotropic materials under mixed-mode loading and provide a reference for standardization in the process.
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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 | 0.001 |
| 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) | 0.003 | 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".