2nd Gen FeCrAl ODS Alloy Development For Accident-Tolerant Fuel Cladding
Bibliographic record
Abstract
Extensive research at ORNL aims at developing advanced low-Cr high strength FeCrAl alloys for accident tolerant fuel cladding. One task focuses on the fabrication of new low Cr oxide dispersion strengthened (ODS) FeCrAl alloys. The first Fe-12Cr-5Al+Y2O3 (+ ZrO2 or TiO2) ODS alloys exhibited excellent tensile strength up to 800 C and good oxidation resistance in steam up to 1400 C, but very limited plastic deformation at temperature ranging from room to 800 C. To improve alloy ductility, several fabrication parameters were considered. New Fe-10-12Cr-6Al gas-atomized powders containing 0.15 to 0.5wt% Zr were procured and ball milled for 10h, 20h or 40h with Y2O3. The resulting powder was then extruded at temperature ranging from 900 to 1050 C. Decreasing the ball milling time or increasing the extrusion temperature changed the alloy grain size leading to lower strength but enhanced ductility. Small variations of the Cr, Zr, O and N content did not seem to significantly impact the alloy tensile properties, and, overall, the 2nd gen ODS FeCrAl alloys showed significantly better ductility than the 1st gen alloys. Tube fabrication needed for fuel cladding will require cold or warm working associated with softening heat treatments, work was therefore initiated to assess the effect of these fabrications steps on the alloy microstructure and properties. This report has been submitted as fulfillment of milestone M3FT 16OR020202091 titled, Report on 2nd Gen FeCrAl ODS Alloy Development for the Department of Energy Office of Nuclear Energy, Advanced Fuel Campaign of the Fuel Cycle R&D program.
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) | 0.001 | 0.001 |
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".