Fully Reversed Uniaxial Tension-Compression High Cycle Fatigue Behaviour of Shot-Peened Steels
Bibliographic record
Abstract
The effect of shot-peening on the uniaxial fatigue behaviour of four engineering steels, heat treated to a similar final hardness was investigated. Forged 0.39%C and 0.72%C steels, a quenched and tempered 0.51%C steel and a 0.50%C powder forged (PF) steel were fatigue tested under fully reversed (R=-1) push-pull loading conditions. Following long life (107) cycling, shot-peening had little effect on the fatigue limit of the 0.39%C and 0.72%C steels whereas the fatigue limit of the PF steel increased 10.4%. Conversely, the fatigue limit of the quenched and tempered steel decreased 12.0% after shot-peening. The results showed that the beneficial effects of shot-peening, such as compressive residual stresses and work hardening, balanced the effects of surface roughness since crack initiation tended to occur below the surface. Microhardness profiles showed that the greatest amount of cyclic softening in the shot-peened regions occurred in the hot rolled steels. Softening was accompanied by a decrease in the depth of surface hardness.
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 | 0.001 |
| 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) | 0.002 | 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".