Editorial: Special Issue on Fatigue and Fracture Mechanics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study of fatigue and fracture behaviors in engineered components remains a critical area across multiple disciplines. Limits on materials behavior are among the most significant technical challenges to enhancing the safety and reliability of engineering systems. Thus, accurately defining recent advancements in analytical methods and testing techniques within fatigue and fracture mechanics for engineered structures, components, and materials is essential. This analysis encompasses both experimental research and recent developments in modeling approaches. Key areas of interest include applications of emerging analytical tools and novel experimental techniques to assess and improve durability and damage tolerance using multiscale or multiphysics-based approaches; studies on the effects of additive manufacturing processes on fatigue and fracture properties; and implications of improved modeling and experimental capabilities on fatigue life forecasting and structural health monitoring strategies. In this context, a special issue in Materials Performance and Characterization offers readers valuable insights for their research. The call for papers attracted high-quality contributions from leading scientists and engineers resulting in 11 full-length manuscripts. The main topics covered include fatigue crack growth fracture, propagation, toughness fatigue, and damage failure inspection repair. The editorial teams extend their heartfelt thanks to the authors and reviewers for their dedication and to the ASTM staff for their support in bringing this issue to publication. We hope these papers provide valuable contributions to ongoing research efforts in fatigue and fracture mechanics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it