Modeling Thermomechanical Cyclic Deformation by Evolution of Its Activation Energy
Bibliographic record
Abstract
This paper presents a new approach for modeling the deformation response of metallic materials under thermomechanical fatigue loading conditions, based on the evolution of thermal activation energy. In its physical essence, inelastic deformation at high temperatures is a thermally activated process. The thermal activation energy, which controls the time and temperature dependent deformation behavior of the material, generally evolves with the deformation state (γp) of the material, in response to the applied stress τ. In the present approach, the inelastic flow equation is integrated for a deformation range where strain hardening is predominant. The simplified integration version of the model only needs to be characterized/validated by isothermal tensile and fatigue testing, and it offers an explicit description of the TMF behavior in terms of physically defined variables. By identifying the dependence of these variables on the cyclic microstructure, the model may also offer a mechanistic approach for fatigue life prediction.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 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".