Power Cycles of Generation III and III+ Nuclear Power Plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is well known that the electrical-power generation is the key factor for advances in any other industries, agriculture and level of living. In general, electrical energy can be generated by: 1) non-renewable-energy sources such as coal, natural gas, oil, and nuclear; and 2) renewable-energy sources such as hydro, wind, solar, biomass, geothermal and marine. However, the main sources for electrical-energy generation are: 1) thermal - primary coal and secondary natural gas; 2) “large” hydro and 3) nuclear. The rest of the energy sources might have visible impact just in some countries. Modern advanced thermal power plants have reached very high thermal efficiencies (55–62%). In spite of that they are still the largest emitters of carbon dioxide into atmosphere. Due to that, reliable non-fossil-fuel energy generation, such as nuclear power, becomes more and more attractive. However, current Nuclear Power Plants (NPPs) are way behind by thermal efficiency (30–42%) compared to that of advanced thermal power plants. Therefore, it is important to consider various ways to enhance thermal efficiency of NPPs. The paper presents comparison of thermodynamic cycles and layouts of modern NPPs and discusses ways to improve their thermal efficiencies.
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.
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 | 0.000 | 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 it