Driving Force and Logic of Development of Advanced High Strength Steels for Automotive Applications
Bibliographic record
Abstract
Abstract The major scientific and technological advances and breakthroughs of advanced high strength steels (AHSS) were achieved due to the strong demands of automotive industry. The development of AHSS began in the early 1980s with the aim of improving passenger safety and weight‐saving. The present paper presents the driving forces and logic of development of various AHSS for automotive applications since 1980s. The importance of crash performance, weight‐saving, formability, and rigidity are critically reviewed for the development of new steel grades for automotive applications. The logical sequences of the development of dual phase (DP) steel, transformation induced plasticity (TRIP) steels, tempered DP steels, complex phases (CP) steels, Ferrite‐Bainite steels, hot‐stamping technology, twinning induced plasticity (TWIP) steels, Quench and Partitioning (Q&P) steels, Medium Mn steels, and steels–polymer composites are presented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".