Fatigue life prediction of beam structures with breathing cracks using finite element analysis
Bibliographic record
Abstract
This study presents a numerical procedure for estimating the fatigue life of cracked beams subjected to two-dimensional (2D) and three-dimensional (3D) direct and/or base excitations. A finite element (FE) model is developed for a cracked beam, in which the stiffness matrix of the beam element containing a breathing crack is formulated based on its strain state. Using this model, the stress intensity factor is computed for each vibration cycle, accounting for the breathing behavior of the crack. Fatigue crack growth increments are then evaluated using Walker’s equation to determine the total crack growth life and the maximum stress intensity factor. The fatigue status of the beam is assessed using three defined failure criteria. The proposed computational procedure is validated through two case studies involving a simply supported beam and a fixed-fixed beam, both containing breathing cracks. The maximum prediction error compared with experimental results is 7.91 %, demonstrating the method’s high accuracy. This work provides an effective and generalizable FE-based framework for fatigue life prediction of dynamically loaded beam structures with breathing cracks.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".