Uniaxial fracture and plastic anisotropy characterization of sheet metals using the in-plane bending test
Bibliographic record
Abstract
An in-plane bend test fixture was developed to produce uniaxial tensile and compressive stress states in sheet metals without need for anti-buckling devices while enabling optical strain measurement. An in-plane bend fixture and specimen geometry were developed with emphasis placed upon edge strain measurement and determination of appropriate fracture detection metrics. The proposed specimen geometry was found to reach edge strains of approximately 0.70 and could characterize R-values in uniaxial tension and compression. A so-called arc length method that is based upon geometric changes during in-plane bending was proposed and applied at the convex edge where cracks initiated. The arc length method strains showed excellent agreement with digital image correlation (DIC) and exhibited only mild sensitivity to the optical lengthscale. Various fracture detection methods such as the peak force and bending moment, and metrics based upon a theoretical bending stress and the local strain rate were considered for a third generation 980GEN3 and an MS1500 steel. The force and bending moment were only valid in specific cases while the bending stress and strain rate methods were in close agreement with onset of visible cracking. The 980GEN3 in-plane bending failure limits were in excellent agreement with the conical hole expansion test suggesting a convergence in the uniaxial fracture strains between in-plane and out-of-plane loading when necking is suppressed. Finally, a host of advanced high strength steels with different strengths and thicknesses were tested to assess the sensitivity of the sample geometry to buckling. The gauge-height-to-thickness aspect ratio was the primary factor influencing geometric instability with an aspect ratio of 4.0 or lower recommended to mitigate buckling.
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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 | 0.001 | 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".