Axial fatigue of a gas‐nitrided quenched and tempered AISI 4140 steel: effect of nitriding depth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Fatigue testing under fully reversed axial loading ( R =−1) and zero‐to‐tension axial loading ( R = 0) was carried out on AISI 4140 gas‐nitrided smooth specimens. Three different treatment durations were investigated in order to assess the effect of nitriding depth on fatigue strength in high cycle fatigue. Complete specimens characterization, i.e., hardness and residual stresses profiles (including measurement of stabilized residual stresses) as well as metallographic and fractographic observations, was achieved to analyse fatigue behaviour. Fatigue of the nitrided steel is a competition between a surface crack growing in a compressive residual stress field and an internal crack or ‘fish‐eye’ crack growing in vacuum. Fatigue life increases with nitriding depth until surface cracking is slow enough for failure to occur from an internal crack. Unlike bending, in axial fatigue ‘fish‐eye’ cracks can initiate anywhere in the core volume under uniform stress. In these conditions, axial fatigue performance is lower than that obtained under bending and nitriding depth may have no more influence. In order to interpret the results, special attention was given to the effects of compressive residual stresses on the surface short crack growth (closure effect) as well as the effects of internal defect size on internal fatigue lives. A superimposed tensile mean stress reduces the internal fatigue strength of nitrided steel more than the surface fatigue strength of the base metal. Both cracking mechanisms are not equally sensitive to mean stress.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it