Modeling and Experimental Assessment of Bending Characteristics of Laminated Bilayer Sheet Materials
Bibliographic record
Abstract
Many mathematical models based on the advanced theory of bending to predict bending characteristics for monolithic sheet materials are available in the literature. In this work, a similar approach is utilized to develop bending models for a bilayer laminated sheet material. The principal stresses and strains through the thickness and change in relative thickness, at specified bend curvatures, are obtained as a function of increasing curvature during bending. Additionally, three-dimensional (3D) finite element (FE) based models for bilayer laminate bending are developed to overcome simplifications of the analytical models. In order to experimentally validate the two models, a new experimental bend test-jig is developed and experiments are performed on bilayer steel–aluminum laminate for different clad to matrix thickness ratios. These experiments have enabled continuous measurements of strain along the width at the bend line and through the laminate thickness at one of the specimen edges using an online strain mapping system based on digital image correlation (DIC) method. Analytical model results indicate how the through-thickness strain distribution and relative thickness of the specimen in bending are influenced by the location and thickness of the soft clad material. The FE model and experimental results exhibit similar trends in the relative thickness change for different geometric arrangements of steel–aluminum layers. The tangential and radial stresses decrease in magnitude with increasing aluminum clad thickness ratios. The 3D FE model of laminate bending provided strain predictions across the specimen width at the bend line on the tension and compression sides that increased with increasing clad thickness ratios. Also, relative thickness data from the 3D FE model showed uniaxial and plane strain stress states at the edge and midwidth sections of the test specimen. The results from analytical and FE models and from DIC and microscopic thickness measurements indicate that thickness at the bend line increases with increasing clad thickness for the case of clad layer on the compressive side of the laminate (i.e., C-C case) and vice versa for clad layer on the tensile side (C-T).
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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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".