Strain rate effects for aluminum and magnesium alloys in finite element simulations of steering wheel armature impact tests
Bibliographic record
Abstract
ABSTRACT This paper addresses the strain rate effects for aluminum and magnesium steering wheel armatures when they are subjected to dynamic impact tests. Two geometrically different steering wheel armatures, a three spoke proprietary aluminum alloy armature and a four spoke magnesium alloy (AM50A) armature, underwent experimental impact testing. The testing conditions for each armature were different; testing with the aluminum alloy armature involved impacts with a deformable chestform and the magnesium armature experienced impact tests with a rigid plate. Finite element models of all testing apparatuses were developed for both testing conditions and numerical simulations were conducted based on the experimental method employed. Strain rate effects for the aluminum alloy were considered using the Cowper–Symonds constitutive relation and a Johnson–Cook material law was utilized for the magnesium alloy. Simulations were conducted with and without strain rate effects considered. The comparison between the experimental and numerical methods illustrate that there is only a minor change in the numerical testing results with the inclusion of strain rate effects, however, a better correlation between experimental and numerical methods occurs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".