The Effect of Periodic Overloads on Biaxial Fatigue of Normalized SAE 1045 Steel
Bibliographic record
Abstract
During the past decade it has been observed that periodically applied overloads of yield stress magnitude can significantly reduce or eliminate crack closure under uniaxial or Mode I loading. This paper reports the results of a series of biaxial in-phase tension-torsion experiments that were performed to evaluate the effects of overloads on the fatigue life of smooth tubes constructed of normalized SAE 1045 steel. Five strain ratios were investigated, including uniaxial (λ = εxy/εxx = 0), pure torsion (λ = ∞), and three intermediate ratios (λ = 3/4, 3/2, and 3). Periodically applied overloads of yield stress magnitude allowed cracks to grow under crack face interference-free conditions. Strain-life curves were developed by computationally removing the overload cycle damage from test results and calculating equivalent fatigue lives. A factor of two reduction in the fatigue limit was found at all ratios when these results were compared with constant-amplitude results. Cracking behavior was observed and it was noted that for strain ratios greater than one, cracks initiated along the rolling direction (longitudinally); otherwise, the cracks initiated on maximum shear planes. This observation was used to help explain the similarity in fatigue life results for all strain ratios for both constant-amplitude and overload data. Parameter-life curves were developed using the equivalent fatigue life data and several common multiaxial damage parameters, and the damage parameters were evaluated. It was found that the simple maximum shear strain criterion together with uniaxial overload data provided a good estimate of the fatigue behavior for all strain ratios.
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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 | 0.000 | 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".