A Mechanism-Based Approach From Low Cycle Fatigue to Thermomechanical Fatigue Life Prediction
Bibliographic record
Abstract
Deformation and damage accumulation occur by fundamental dislocation and diffusion mechanisms. An integrated creep–fatigue theory (ICFT) has been developed, based on the physical strain decomposition rule that recognizes the role of each deformation mechanism, and thus relate damage accumulation to its underlying physical mechanism(s). The ICFT formulates the overall damage accumulation as a holistic damage process consisting of nucleation and propagation of surface/subsurface cracks in coalescence with internally distributed damage/discontinuities. These guiding principles run through both isothermal low cycle fatigue (LCF) and thermomechanical fatigue (TMF) under general conditions. This paper presents a methodology using mechanism-based constitutive equations to describe the cyclic stress–strain curve and the nonlinear damage accumulation equation incorporating (i) rate-independent plasticity-induced fatigue, (ii) intergranular embrittlement (IE), (iii) creep, and (iv) oxidation to predict LCF and TMF lives of ductile cast iron (DCI). The complication of the mechanisms and their interactions in this material provide a good demonstration case for the model, which is in good agreement with the experimental observations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".