Bibliographic record
Abstract
The first works devoted to the problem of heat transfer at supercritical pressures started as early as the 1930s. E. Schmidt and his associates investigated free-convection heat transfer to fluids at the near-critical point with the objective of developing a new effective cooling system for turbine blades in jet engines. In the 1950s, the idea of using supercritical “steam”-water appeared to be rather attractive for steam generators / turbines to increase thermal efficiency of fossil-fired power plants. Intensive work on this subject was mainly performed in the former USSR and in the USA in the 1950s–1980s. Therefore, the most investigated flow geometry at supercritical pressures is circular tubes with water as the coolant. Currently, using supercritical “steam” in fossil-fired power plants is the largest industrial application of fluids at supercritical pressures. At the end of the 1950s and the beginning of the 1960s, some studies were conducted to investigate the possibility of using supercritical water as a coolant in nuclear reactors. Several concepts of nuclear reactors were developed. However, this idea was abandoned for almost 30 years, and then regained momentum in the 1990s as a means to improve the performance of water-cooled nuclear reactors. Main objectives of using supercritical water in nuclear reactors are increasing the efficiency of modern nuclear power plants, which is currently 30–35%, to circa 43–50%, and decreasing operational and capital costs by eliminating steam generators, steam separators, steam dryers, etc. Therefore, objectives of the current paper are to assess the work that was performed and to understand specifics of heat transfer at supercritical pressures.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".