Postbuckling response of composite laminated plates with evolving damage
Bibliographic record
Abstract
In this paper, postbuckling behavior and progressive failure of laminated plates considering geometric nonlinearity and evolving material damage under uniaxial, biaxial compressive and in-plane shear loadings are studied. The damage model is based on a generalized macroscopic continuum theory within the framework of irreversible thermodynamics and enables to predict the progressive damage and failure load. Damage variables are introduced for the phenomenological treatment of degradation of the stiffness properties of laminated plates due to microscopic defects. The analysis is carried out using field-consistent finite element approach based on first-order shear deformation theory. The nonlinear governing equations are solved using the Newton–Raphson iterative technique coupled with the adaptive displacement control method to trace the pre- and postbuckling equilibrium path. The damage evolution equations are solved at every Gauss point using Newton–Raphson iterative technique within each loading/displacement increment iteration. The detailed parametric study is carried out to investigate the influences of evolving damage, span-to-thickness ratio, lamination scheme, boundary conditions and aspect ratio on the postbuckling response and failure load of laminated plates under in-plane loading. The ratio of failure load to buckling load increases with increase in thickness ratio due to the dominating restoring action of in-plane stretching forces in postbuckling region of thin plates whereas the thick plates depict material failure prior to buckling point. Thin plates with SSFF boundary conditions with evolving damage depict softening postbuckling response whereas the plates with other boundary conditions considered depict hardening response.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".