Characterization of shear and bending stiffness for optimizing shape and material of lightweight beams
Bibliographic record
Abstract
Optimized slender and short-thick beams are used in building, aircraft and machine structures to increase performance at a lower material cost. A previous work proposes an optimum shape, material and size selection model to design lightweight slender beams under pure bending. In short-thick beams, the transverse shear effects are no longer negligible and impact the choice of the optimum shape. This work extends such an optimum selection model to consider both slender and short-thick beams, by formulating the total beam stiffness design requirement as a combination of shear and bending stiffness. Selection charts are developed to show the impact of design variables, such as shape, size, material and slenderness, on the total beam stiffness. The model of total beam stiffness is validated against computational results from finite element analyses of beam models. A case study demonstrates the use of the selection charts to compare the performance of beams at the conceptual design stage.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".