Integration of Fatigue R-Curve Effects into VCCT for Durability Predictions, Part 1: Buckled Composite Single-Stringer Stiffened Panels
Why this work is in the frame
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Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-0952.vid Composite structures have become popular in modern aircraft because they help reduce weight and increase durability. In addition, hat-stiffened panels provide the stability that the airframe skin needs. However, they can be subject to delamination in the post-buckling regime. Progressive damage analysis (PDA) methods can help predict interlaminar and intralaminar failure events. Many aircraft structures are subject to cyclic loading in the post-buckling regime. Hence, fatigue life prediction becomes essential for design and sustainment purposes. Under the NASA Advanced Composites Project (ACP), composite panels stiffened with single hat-stringers were subject to a cyclic loading sequence from a pre-buckling state to a post-buckling state. This test campaign aimed to provide damage initiation and growth data for three initial damage scenarios: nominally pristine, initial Teflon inserts representing manufacturing defects, and impact-induced damage. This work uses the Abaqus FEA Virtual Crack Closure Technique (VCCT), capabilities enhanced through a novel empirical method integrating fatigue R-curve effects (different from R-ratio) into the Paris Law via user-defined subroutine to simulate the fatigue response of the panels with single hat-stringers. The analysis predictions were within 5% of the test results using this novel method.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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