Effects of working conditions on the performance of an ammonia ejector used in an ocean thermal energy conversion system
Bibliographic record
Abstract
Abstract Ocean thermal energy has attracted much attention for its huge potential resources. It's proved that an ocean thermal energy conversion (OTEC) cycle system using ammonia ejectors is beneficial to improve the cycle efficiency. Thus, the performance of an ammonia ejector is studied numerically in this paper. Effects of working conditions which occurred inside the ammonia ejector, like primary flow pressure (1.3‐2.1 MPa), secondary flow pressure (0.45‐0.65 MPa), and back pressure (0.5‐1.05 MPa), on the mixing process and flow phenomenon, are discussed in detail. The results demonstrate that the entrainment ratio of ammonia ejector ranging from 0.35‐0.65 increases with decreasing primary flow pressure at the critical working mode, while the reverse is true for the critical back pressure. Two small vortexes are formed near the ejector wall due to the boundary layer separation when the ejector works at the subcritical or critical mode. These vortexes reduce the effective area and flow rate of the secondary flow. The Ma contours are nearly the same in the nozzle and mixing zone for the critical and subcritical mode, but distributions of Ma vary dramatically in the diffuser corresponding to the variation of secondary series of oblique shock.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".