Innovative Flexible Metal Forming Processes based on Hybrid Thermo‐Mechanical Interaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A new approach towards functional gradation of structural parts is presented. This approach is based on the utilization of locally varying thermo‐mechanically coupled effects applied to different initial workpiece geometries. The possible degree of freedom for the gradation of material properties and geometrical shape for sheet metal forming applications as well as for parts produced by bulk metal forming is characterized by the results of metallographic investigations, by mechanical testing and by an indication of the remaining residual stress state. On the basis of experimental results and process simulations, it could be revealed that the ability to exactly control the dynamic microstructural evolution by thermal and mechanical process parameters combined with predefined material design parameters constitutes a key towards the adjustment of flexible material property profiles even for parts with complex three‐dimensional geometry. Beyond that, the integrative aspect of thermal and mechanical treatment already implies the high level of obtainable efficiency resulting from shortening of process chains. However, it is not only the ability to integrate shape generation and property gradation, but also the automatically included positive effect of tailoring process behaviour by a gradation of formability finally allowing to improve process efficiency e.g. by a reduction of forming steps or reduction of (local) tool load.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it