Bibliographic record
Abstract
The linear finite element analysis of solids and structures are discussed in the first part of the report. Thefinite element formulations for a three dimensional problem is derived and significant issues are addressed.Three dierent types of elements, the bilinear iso-parametric quadrilaterals, the quadratic triangles andthe linear tetrahedrons are used to solve a linear plate problem and the results are compared.The analysis of a common geometric nonlinearity encountered in structural mechanics is dealt with in thesecond part of the report. A brief introduction to nonlinear analysis is provided, while the geometric nonlinearityis discussed in detail. Timoshenko beam analysis is considered as the one dimensional version ofReissner-Mindlin plate theory and the nonlinear strain-displacement relation are treated in an appropriateway to avoid unrealistic simplifications. The force vector and tangent stiffness matrix are derived andthe formulation is extended to implement the trigonometric basis functions. A major issue in geometricnonlinear analysis, namely locking, is addressed and reduced order integrations are implemented to avoidthe consequences. The convergence of the model is checked with available analytical solutions. An Eulermethod in combination with Newton-Raphson method is used to fully analyze the geometric nonlinearity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".