The Effect of Biaxial Strain Ratio and Periodic Compressive Overstrains on Fatigue Crack Growth Mode and Crack Growth Rate
Bibliographic record
Abstract
Biaxial fatigue tests were performed on thin-walled tubular 1045 steel specimens in a test fixture that applied internal and external pressure and axial load. There were two test series, one in which constant amplitude fully reversed strains were applied and another in which large periodic compressive strain cycles causing strains normal to the crack plane were inserted in a constant amplitude history of smaller strain cycles. Ratios of hoop strain to axial strain of λ = - 1 (pure shear), λ = -0.625, λ = - v (uniaxial straining), and λ = +1 (equibiaxial straining) were used in each test series. A confocal scanning laser microscopy (CSLM) image processing technique that gave a resolution of 0.25 μm was developed and used to obtain three-dimensional images of small cracks as they were opened under load. The information in the images was used to construct cross sections of cracks from which crack depth, shape and crack opening stress were obtained. For pure shear straining tests (λ = -1) and for tests at a strain ratio of λ - 0.625 surface cracks rapidly initiated on planes of maximum shear in both constant amplitude and overstrain tests but did not increase significantly in length until near the end of the tests. Instead they grew into the specimen until they were semi-circular in shape. This phase occupied approximately 90% of the fatigue life. Then they began to grow in length as well as depth and linked up to cause failure. In the uniaxial and equibiaxial straining tests, crack growth initiated on planes of maximum shear at 45° to the surface of the specimens (Stage I crack growth) before changing to Stage II growth perpendicular to the applied stress. The cracks once initiated grew continuously in both the length and depth direction until failure took place. The magnitude and frequency of application of the periodic compressive overstrain cycles in the second test series was chosen to reduce the crack opening stress level below the minimum stress level of the constant amplitude cycles so that they experienced closure-free crack growth. The compressive overstrains significantly increased crack growth rates and decreased the threshold strain intensity for the smaller constant amplitude cycles. They also caused a large decrease in the small cycle fatigue resistance as measured by their equivalent strain-life curves.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".