An Analysis Procedure to Verify Delamination Modelling Using Cohesive Elements
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2021-1165.vid A parametric study was conducted to assess the applicability of using cohesive elements to model the progressive failure behaviour of a unidirectional composite double cantilever beam (DCB) specimen. A verification procedure to identify acceptable modelling predictions with limited experimental data is presented. The verification principle is based on the inherent equality relationship between the input and the calculated output DCB material fracture toughness, GIC, values. The output GIC values are calculated using the finite element simulation results in conjunction with the standard ASTM method and with a solution that was developed previously by the National Research Council of Canada (NRC) for unidirectional composite DCB specimens. For the considered case, it was found that the NRC solution provided closer calculated GIC values than the ASTM method, as compared with the input value. Therefore, the acceptability of modelling results were selected based on a prescribed tight GIC agreement that was suggested to be within ±2% using the NRC solution. Within this procedure, very close load-displacement curves and similar crack propagation profiles were obtained from the models based on significantly different mesh sizes and cohesive zone parameters. This finding may significantly improve the modelling efficiency and make progressive failure analysis more practical. For instance, it allows the use of a relatively coarse-mesh model with a small cohesive strength and a high stiffness, rather than a dense-mesh model with a high cohesive strength and low stiffness. A commentary is provided regarding the minimum required number of cohesive elements within the cohesive zone length, and the robustness of modelling using cohesive elements.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".