Advanced Ultra-Supercritical Valve Development Program
Bibliographic record
Abstract
Abstract Materials are the key to develop advanced ultra-supercritical (A-USC) steam generators. Operating at temperature up to 760°C and sustained pressure up to 4500 psi. Pressure vessel and piping materials may fail due to creep, oxidation, and erosion. Valves are particularly subjected to loss of function and leakage due to impermeant of the sealing surfaces. New materials, less susceptible to the above damage modes are needed for A-USC technology. Two Ni-based superalloys have been identified as prime candidates for valves based materials. Hardfacing is applied to sealing surfaces to protect them from wear and to reduce friction. Stellite 6 (Cobalt-based alloy) is the benchmark hardfacing owing to its anti-galling properties. However, the latest results tend to indicate that it is not suitable for high pressure application above 700°C. An alternative hardfacing will be required for A-USC. New Ni- and Co- based alloys are being developed for applications where extreme wear is combined with high temperatures and corrosive media. Their chemistry accounts for the excellent dry-running properties of these alloys and makes them very suitable for use in adhesive (metal-to- metal) wear. These new alloys have better wear, erosion, and corrosion resistance than Stellite 6 in the temperature range 800°C ~ 1000°C. As such, they have the potential to operate in A-USC. Velan recently developed an instrumented high temperature tribometer in collaboration with Polytechnique Montreal to characterize new alloys including static and dynamic coefficients of friction up to 800°C. We present herein the methodology that has been devolved to explore the effects of elevated temperature on the tribological behavior of those advanced material systems, with the goal of capturing the basis for the specification, design, fabrication, operation, and maintenance of valves for A-USC steam power plants.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".