Modeling of Strength Differential Effects in HCP Sheet Materials
Bibliographic record
Abstract
A simple approach is proposed to employ symmetric yield functions for modeling the tension-compression asymmetry commonly observed in hcp materials. In this work, the strength differential (SD) effect is modeled by choosing separate symmetric plane stress Barlat Yld 2000 yield functions for the tension i.e., in the first quadrant of principal stress space, and compression i.e., third quadrant of principal stress space. In the second and fourth quadrants, the yield locus is constructed by adopting Bézier interpolating functions between uniaxial tensile and compressive stress states. The main advantage of this proposed approach is that the yield locus parameters are deterministic and relatively easy to identify when compared to the Cazacu-Plunkett-Barlat (CPB) family of yield functions commonly used for modeling the SD effect observed in hcp materials. The proposed yield function is implemented as a user material subroutine (UMAT) within the commercial finite element software, LS-DYNA. The predictions of the developed material model are compared with the measured load-displacement and strain distributions from a three-point bend experiment on AZ31B sheet.
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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 | 0.001 | 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".