Solutions and applications of fracture properties for clamped single edge notched tensile specimen of orthotropic materials
Bibliographic record
Abstract
Abstract Clamped single edge notched tensile (SENT) specimens are widely used in fracture toughness test and fatigue crack growth experiment of structural materials. However, the existing fracture parameters of clamped SENT specimens are all based on isotropic conditions, which limits the application of anisotropic materials. In this study, a systematic finite element analysis of orthotropic clamped SENT specimens was carried out to determine the stress intensity factor ( K ) and compliance ( C ). A wide range of orthotropic and geometric parameters, including crack length over width ratio ( a / W ), daylight to width ratio ( H / W ), and material parameters λ and ρ , were considered. The coupling effects of material parameters and geometrical dimensions on fracture properties were then investigated. Results showed that the K and C increase with the increase of a / W and H / W , and decrease with the increase of λ and ρ . The value of C is more sensitive to changes of orthotropic and geometric parameters than the K . Moreover, the accurate solutions for normalized K , C and compliance‐based crack length prediction were developed. Applications of the proposed solutions on experimental data were presented and discussed. The current results will help to accurately calculate the fracture toughness or FCG rate of composites, further advancing the standardization process of composites testing based on SENT specimens. Highlights Evaluate the K and Compliance for orthotropic single edge notched tensile (SENT) specimens using 2D finite element analysis; The coupling effects of orthotropic parameters and geometric sizes are studied; Develop prediction equations for K and C of clamped SENT specimen; Propose a universal crack length estimation method based on the compliance; Discuss the application of the proposed equations to the tested data of UD CFRP.
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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 | 0.001 | 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".