Application of Supercritical Pressures in Power Engineering
Bibliographic record
Abstract
SuperCritical Fluids (SCFs) have unique thermophyscial properties and heat-transfer characteristics, which make them very attractive for use in power industry. In this chapter, specifics of thermophysical properties and heat transfer of SCFs such as water, carbon dioxide and helium are considered and discussed. Also, particularities of heat transfer at SuperCritical Pressures (SCPs) are presented, and the most accurate heat-transfer correlations are listed. SuperCritical Water (SCW) is widely used as the working fluid in the SCP Rankine “steam”-turbine cycle in fossil-fuel thermal power plants. This increase in thermal efficiency is possible by application of high-temperature reactors and power cycles. Currently, six concepts of Generation-IV reactors are being developed, with coolant outlet temperatures of 500°C~1000°C. SCFs will be used as coolants (helium in GFRs and VHTRs; and SCW in SCWRs) and/or working fluids in power cycles (helium; mixture of nitrogen (80%) and helium [20%]; nitrogen, and carbon dioxide in Brayton gas-turbine cycles; and SCW “steam” in Rankine cycle).
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".