Investigation of the Axial and Torsional Low-Cycle Fatigue Properties of Notched High Strength Steels for Application to Landing Gear Fuse Pins
Bibliographic record
Abstract
Accurate and reliable fuse pin fatigue life estimates are a priority for public safety; however, development of a comprehensive parametric model remains a significant engineering challenge.This work assessed the usage of parametric uniaxial strain life models for multiaxial life prediction induced by notches for application to fuse pins.AISI 4340 and 300M steel coupons were tested under pure axial and pure torsional loading with fully-reversed, mean stress, and residual stress conditions.Residual stresses had a negligible effect on axial and torsional fatigue lives due to stress relaxation, while mean stresses either quadrupled (compressive) or at least halved (tensile/torsional) fatigue life.The strain life prediction model effectively predicted axial fatigue lives, although results were sensitive to the fatigue ductility exponent.Shear strain life models were nonconservative for predicting low-cycle fatigue life in torsion.Future work should consider scale and environmental effects when applying these findings to fuse pin fatigue design.
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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".