Warm Forming Simulation of a ZEK100 Magnesium Door Panel
Bibliographic record
Abstract
Abstract The warm forming of a door panel made of commercial grade ZEK100 magnesium alloy sheet was modelled using finite element techniques (Autoform). The operation consisted of a heating step, a forming step and a cooling/springback step. The material properties of the ZEK100 blank were modelled using a set of temperature- and strain rate-dependent stress-strain curves, which were derived based on a Zerilli-Armstrong constitutive model. In order to simplify the material model to enable its complex response to be represented within a commercial finite element code, the anisotropy of the magnesium sheet was approximated using a Banabic-2005 yield surface and yield asymmetry was neglected, a reasonable approach for warm forming. Necking was predicted using a set of forming limit curves obtained at different isothermal temperatures. The entire forming model was run at a punch speed of 160 mm/s, and two initial blank temperatures: 215 and 230 °C. The tooling was initially at room temperature. The model predicted that the blank cracked when its initial temperature was 215 °C due to excessive cooling. The best formability (lack of wrinkling and necking) was predicted when the blank was heated to 230 °C. These predictions agree well with the forming trial outcomes.
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 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 | 0.001 | 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 | 0.001 |
| 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 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".