Finite Element Analysis Simulation of the Effect of Induction Hardening on Rolling Contact Fatigue
Bibliographic record
Abstract
The objective of this research is to conduct a finite element analysis to better understand the effects of induction hardening on rolling contact fatigue (RCF). The finite element analysis was developed in three-dimensional to estimate the maximal loading and the positions of the crack nucleation sites in the case of cylinder contact rolling. Rolling contact with or without surface compressive residual stress (RS) were studied and compared. The RS profile was chosen to simulate the effects of an induction hardening treatment on a 48 HRC tempered AISI4340 steel component. As this hardening process not only generates a RS gradient in the treated component but also a hardness gradient (called over-tempered region), both types of gradients were introduced in the present model. RSs in compression were generated in the hard case (about 60 HRC); tension values were introduced in the over-tempered region, where hardness as low as 38 HRC were set. In order to estimate the maximal allowable loadings in the rotating cylinders to target a life of 106 cycles, a multiaxial Dang Van criterion and a shear stress fatigue limit were used in the positive and negative hydrostatic conditions, respectively. With the proposed approach, the induction hardened component was found to have a maximal allowable loading significantly higher than that obtained with a nontreated one, and it was observed that the residual tensile stress peak found in the over-tempered region could become a limiting factor for fatigue rolling contact life.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".