Cylindrical cup deep drawing of ZEK100 sheet at elevated temperatures
Bibliographic record
Abstract
Cylindrical cup deep drawing experiments are performed on as-received magnesium rare-earth alloyed ZEK100 rolled sheet between room temperature and 250 °C. All tests are performed using warm tooling comprising a 101.6 mm (4") diameter cylindrical punch and smooth die and blank holder. Both isothermal and non-isothermal experiments are performed with a draw ratio of 2.25. Warm temperature formability of ZEK100 is investigated through determination of draw depths of cylindrical cups under isothermal and non-isothermal conditions. The effect of sheet anisotropy during deep drawing operation is investigated by measuring the earring profiles by means of digital imaging as well as sheet thickness from the center to the outer diameter in the rolling direction. It is found that ZEK100 sheets exhibit significantly better warm temperature drawing performance over commercial wrought magnesium alloy sheet – e.g. a full draw of 203.2 mm (8") blanks of ZEKIOO-O was achieved with tool temperature of 150 °C compared to a full draw for AZ31B-O with a tool temperature of 225 °C. Temperature process windows are used to present a direct comparison of forming behavior between ZEK100 and AZ31B. The increased forming performance of ZEK100 at elevated temperatures is attributed to the weakened texture resulting from alloying with Zr and Nd, respectively, allowing for elevated slip activity at lower temperatures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".