Experimental and Numerical Fracture Characterization of DP1180 Steel in Combined Simple Shear and Uniaxial Tension
Bibliographic record
Abstract
Current tests for plane stress characterization of fracture in automotive sheet metals include simple shear, uniaxial, plane strain, and biaxial tension, but there is a significant gap between shear and uniaxial tension. Presently, it remains uncertain whether the fracture strain experiences a reduction between simple shear and uniaxial tension or undergoes an exponential increase as the triaxiality decreases. Fracture in combined simple shear and tension is complicated by premature edge cracking in tension along with a strong sensitivity of fracture strain to the measurement lengthscale. To address these issues, several existing simple shear geometries were modified and evaluated, with a focus on obtaining approximately linear strain paths corresponding to combined uniaxial tension and simple shear suitable for experimental fracture characterization using digital image correlation (DIC). An experimental and numerical investigation was conducted using two planar geometries that do not require through-thickness machining and can be easily tested on a universal test frame. Finite-element analysis was used to investigate the influence of the notch eccentricity on the stress state and predicted fracture location. The most promising geometry in each coupon type was then selected and tested for a dual-phase advanced high-strength steel, DP1180. The performance of the two planar geometries was evaluated based on the linearity of strain and stress state, along with the location of fracture initiation. The best geometry was then used to evaluate and recalibrate the modified Mohr-Coulomb (MMC) fracture locus with data in combined shear and tension. The initial MMC calibration using four fracture tests that suppressed necking provided an accurate estimate for the fracture strain in combined uniaxial tension and simple shear. The MMC model correctly predicted a valley in the fracture strain between these two loading conditions.
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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) | 0.000 | 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 | 0.000 | 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".