Optimization of Perfect and Imperfect Ring and Stringer Stiffened Cylindrical Shells with PANDA2 and Evaluation of the Optimum Designs with STAGS
Bibliographic record
Abstract
Ring and stringer stiffened perfect and imperfect angle-ply cylindrical shells under combined axial compression and in-plane shear are optimized with a program called PANDA2 for the minimum weight design of stiffened panels, and the optimum designs are then evaluated with use of a general purpose finite element code called STAGS. The good agreement between PANDA2 and STAGS predictions for the nonlinear collapse of imperfect stiffened shells justifies the use of PANDA2 for preliminary design. A new PANDA2 processor called STAGSUNIT automatically generates STAGS input files for cylindrical panels and shells with both stringers and rings that have various open cross sections such as Blades, Zees, Jays, Tees and Is. In STAGSUNIT the edge conditions are formulated so that STAGS models of subdomains of a long cylindrical shell with many stiffeners can be constructed that do not have artificial prebuckling stress concentrations near the edges that might significantly affect predictions of bifurcation buckling and nonlinear collapse of the subdomain. Many STAGS models of optimized shells and subdomains of shells with Blade, Zee, and Tee stiffening are generated and explored, both with respect to linear bifurcation buckling and nonlinear collapse. The behavior of shells with an initial imperfection in the form of a general buckling mode of the imperfect shell is described from a physical point of view. Some difficulties encountered during this project are described.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".