Refined design curves for compressive buckling of curved panels using nonlinear finite element analysis
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Bibliographic record
Abstract
The present work deals with implementation of a nonlinear finite element technique for the prediction of the initial buckling in simply-supported curved panels subjected to pure compression. A single nonlinear design curve is derived, representing the compressive buckling stress coefficient as a function of the curved panel parameter for a radius-to-thickness ratio between 1000 and 2000. The proposed curve represents an update and expansion of the currently-used NACA design curves, and it includes the effect of a pre-existing level of imperfection in the panel on the buckling coefficient.The results presented in this work show a strong dependency of the buckling stress on the degree of initial imperfection in the panel, especially for highly-curved panels. The results also indicate that the actual amount of imperfection in a given panel is dependent upon the curved panel parameter and its radius-to-thickness ratio. A detailed knowledge of this dependency would lead to a better prediction of the buckling stress of the panel.
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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) | 0.001 | 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