4E Assessment on Heat Transfer and Optimization of a Novel Cooling-Heating- Power Cogeneration Brayton System
Bibliographic record
Abstract
Abstract High-temperature gas-cooled fast reactors are fourth generation nuclear systems offering ultra-high heat source temperature and advanced safety features. When used in applications such as marine propulsion, delivery of cooling and hot water may be achieved by utilizing reactor heat rejection. The supercritical CO2 Brayton cycle is considered suitable for coupling with the fourth-generation nuclear systems due to the excellent thermophysical properties of supercritical CO2. In this study, a novel cooling-heating-power cogeneration Brayton system that can fully recover the reactor cooling heat is described. The prototype ALLEGRO demonstrator reactor operating conditions are used to design the supercritical CO2 combined cycle. The use of advanced, double-sided etched printed circuit heat exchanger with elliptical channel geometry is examined. Initially, the key thermodynamic and cost metrics are analyzed using energy, exergy, economy, and environment (4E) assessment. Subsequently, multi-objective optimization of the Brayton system is carried out using the 4E metrics. The results show that the economic and environment costs of the combined cycle can be reduced by 2.9% and 49.5%, respectively with respect to the base-case design.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".