On the Measurement of Residual Stress in Induction Hardened Parts
Bibliographic record
Abstract
It is well known that induction surface heating followed by rapid quenching generally increases the fatigue life of steel components subjected to bending loads by significantly postponing the micro-crack nucleation and propagation processes. The phase transformation volume change combined with severe thermal gradients leave a hard surface layer under relatively high and deep compressive residual stresses. In this paper, residual stress measurements are done on induction hardened AMS6414 martensitic steel (aerospace grade of AISI4340) cylinders using two techniques: the so-called contour method and X-ray diffraction. For both methods, induction hardened parts raise many challenges. The contour method hardly describes high stress gradients near the surface while the diffraction technique accuracy appears limited considering the strong microstructural variation and the high depth of the stresses to be measured. For the contour method, a CMM and an optical pen using the confocal chromatic imaging principle were used to measure the surface after precision WEDM cutting. The effect of data filtering and smoothing on the calculated stresses are discussed. For X-ray analysis, the effect of stress relaxation during layer removal and analysis technique is explained. The difference between the residual stress measurements done with the two techniques is discussed with emphasis on both the surface and the in-depth measurements.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".