Novel Concepts for the Application of Magnesium Sheets and Profiles in Crash Loaded Vehicle Areas
Bibliographic record
Abstract
As the lightest structural metal, magnesium alloys have been attractive to reduce vehicle weight and emissions by lightweight design in the automotive industry. Structural crashworthiness is not a physical property itself, but correlates with the material’s ductility and structural design. Magnesium is known to be a material with lower failure strain than other metallic materials. Therefore the use of magnesium in crash-related areas is more challenging compared to steel and aluminum.In structures with a bending load, as in the case of a bumper or the sill, crash properties can be significant improved by filling profiles with a stabilizing core. In order to evaluate the crashworthiness of this hybrid structure under bending loads, both empty and polyurethane foam-filled rectangular section beams were constructed and tested by using the quasi-static/dynamic three-point bending facilities at German Aerospace Centre (DLR) – Institute of Vehicle Concepts.For structures with axial crash loads the normal buckling mode will lead to a very early fracture of the magnesium part. In collaboration with researchers from the University of Windsor and the University of Waterloo, novel technologies for energy absorption which are based on cutting or peeling mechanisms have been developed and investigated, which allow the use of magnesium in these challenging applications. Results of the joint research will be presented.
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 | 0.000 | 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".