Multiaxial fatigue analyses and life predictions using finite element method.
Bibliographic record
Abstract
In predicting the fatigue lives of structural or mechanical components, there are several multiaxial fatigue theories that can be used to evaluate the fatigue crack initiation. However, there exists a lack of agreements on which theory models the fatigue crack initiation most appropriately. The purpose of this thesis is to evaluate the validity of most commonly used multiaxial fatigue criteria; specifically the maximum principal strain and the maximum shear strain criteria. Moreover, a new criterion based on strain energy density is proposed and evaluated for elastic and elastic-plastic damage scenarios. The best criterion, identified through comparative analyses, is used to evaluate the fatigue lives of two connecting rods supplied by an automotive company. Three-dimensional finite element analysis is performed on the SAE notch shaft, which is used as a test component to evaluate the validity of the existing and proposed multiaxial fatigue damage criteria. Elastic and elastic-plastic stress-strain responses are then used to obtain the required damage parameters that are eventually used to predict the fatigue lives. (Abstract shortened by UMI.)Dept. of Mechanical, Automotive, and Materials Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .E45. Source: Masters Abstracts International, Volume: 40-03, page: 0771. Adviser: Sudip Bhattacharjee. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".