In-situ and ex-situ microstructure studies and dislocation-based modelling for primary creep regeneration response of 316H stainless steel
Bibliographic record
Abstract
The emergence of renewable energy sources with their variable and unpredictable nature, in addition to the variation of energy need for weekdays vs. weekends, demands an ever flexible operation of thermal power plants. Such a feature has therefore altered the typical steady creep loading of high-temperature components of power plants to stress-varying or cyclic creep conditions. The introduced load transients have been found to affect the strain hardening memory of the creeping alloys and might lead to multiple primary creep regeneration (PCR). Therefore, the creep strain accumulation can considerably increase under such conditions. Consideration of the PCR phenomenon is beyond the capability of conventional creep constitutive models which are based on strain- or time-hardening assumptions. The present study conducted in-situ and ex-situ experiments for 316H stainless steel. Various microstructural examination techniques, such as synchrotron high energy X-ray and neutron diffraction, and backscattered and transmission electron microscopy, have been employed for characterising evolution of the dislocation structure and the internal lattice strain/stress state of the alloy during stress-varying and cyclic creep conditions. The formation/annihilation of dislocation pileups and the bowing/unbowing of dislocation-lines were identified as the responsible mechanisms for PCR. A dislocation-based model was then formulated which could well represent the measured microstructural evolution and mechanical response of the steel during the conducted experiments at 650°C.
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.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".