Low‐cycle fatigue behavior of a newly developed cast aluminum alloy for automotive applications
Bibliographic record
Abstract
Abstract The drive for increasing fuel efficiency and decreasing anthropogenic greenhouse effect via lightweighting leads to the development of several new Al alloys. The effect of Mn and Fe addition on the microstructure of Al‐Mg‐Si alloy in as‐cast condition was investigated. The mechanical properties including strain‐controlled low‐cycle fatigue characteristics were evaluated. The microstructure of the as‐cast alloy consisted of globular primary α‐Al phase and characteristic Mg2Si‐containing eutectic structure, along with Al8(Fe,Mn)2Si particles randomly distributed in the matrix. Relative to several commercial alloys including A319 cast alloy, the present alloy exhibited superior tensile properties without trade‐off in elongation and improved fatigue life due to the unique microstructure with fine grains and random textures. The as‐cast alloy possessed yield stress, ultimate tensile strength, and elongation of about 185 MPa, 304 MPa, and 6.3%, respectively. The stress‐strain hysteresis loops were symmetrical and approximately followed Masing behavior. The fatigue life of the as‐cast alloy was attained to be higher than that of several commercial cast and wrought Al alloys. Cyclic hardening occurred at higher strain amplitudes from 0.3% to 0.8%, while cyclic stabilization sustained at lower strain amplitudes of ≤0.2%. Examination of fractured surfaces revealed that fatigue crack initiated from the specimen surface/near‐surface, and crack propagation occurred mainly in the formation of fatigue striations.
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 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 | 0.000 | 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) | 0.001 | 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".