Integration of Supercritical CO2 Recompression Brayton Cycle with Organic Rankine/Flash and Kalina Cycles: Thermoeconomic Comparison
Bibliographic record
Abstract
The use of the organic Rankine cycle (ORC), organic flash cycle (OFC) and Kalina cycle (KC) is proposed to enhance the electricity generated by a supercritical CO2 recompression Brayton (SCRB) cycle. Novel comparisons of the SCRB/ORC, SCRB/OFC and SCRB/KC integrated plants from thermodynamic, exergoeconomic and sustainability perspectives are performed to choose the most appropriate bottoming cycle for waste heat recovery for the SCRB cycle. For comprehensiveness, the performance of the SCRB/OFC and SCRB/ORC layouts are examined using ten working fluids. The influence of design parameters such as pressure ratio in the supercritical CO2 (S-CO2) cycle, pinch point temperature difference in heater and pre-cooler 1, turbine inlet temperature and pressure ratio for the ORC/OFC/Kalina cycles are examined for the main system indicators including the net output power, energy and exergy efficiencies, and unit cost of power production. The order of the exergy efficiencies for the proposed systems from highest to lowest is: SCRB/ORC, SCRB/OFC and SCRB/KC. The minimum unit cost of power production for the SCRB/ORC system is lower than that for the SCRB/KC and SCRB/OFC systems, by 1.97% and 0.75%, respectively. Additionally, the highest exergy efficiencies for the SCRB/OFC and SCRB/ORC systems are achieved when n-nonane and R134a are employed as working fluids for the OFC and ORC, respectively. According to thermodynamic optimization design, the SCRB/ORC, SCRB/OFC and SCRB/KC systems exhibit sustainability indexes of 3.55, 3.47 and 3.39, respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".