Constitutive modelling of Usibor® 1500 sheets after intercritical quenching
Bibliographic record
Abstract
Abstract In this study, 0.9 and 1.8 mm thick Usibor® 1500 sheets were subjected to intercritical quenching by heating to 760-930°C and quenching at a controlled rate. The tensile behavior of as-quenched Usibor® 1500 was experimentally obtained using uniaxial tension tests at strain rates ranging from 0.001 to 0.25 s−1. The constants in the hardening models, including Johnson-Cook, were optimized using a Genetic algorithm and linear regression for each condition at each strain rate. Then, these models were numerically modified to account for heat treatment dependency. Uniaxial tensile tests were simulated using the fitted models and compared to experimental flow curves and strain distribution maps to determine the accuracy of the prediction of each model. Optical microscopy was used to determine the volume fraction of each phase using image processing tools and these characteristics were used to explain the behavior of Usibor® 1500 after intercritical quenching. It was found that intercritical quenching process parameters determine the distribution and morphology of each phase and consequently the range of mechanical properties. This model can be used to simulate the deformation of hot-stamped components with tailored properties produced under controlled austenitization.
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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 | 0.000 | 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".