Energetic Optimization and Exergetic Performance Investigation of an Ejector System Using HCFO-1233zd(E) as a Refrigerant
Bibliographic record
Abstract
In this study, the performance of an ejector refrigeration system using HCFO-1233zd(E) as the working fluid is investigated and presented. A novel improved modeling approach that considers ejector loss coefficients as functions of the ejector pressure lift and area ratio has been used. The resulting mathematical model developed using the first and second laws of thermodynamics and gas dynamics is solved using Engineering Equation Solver. Different ejector geometries with area ratios of 6.44, 7.04, 7.51, 7.73, 8.28, 8.62, 9.13, 9.41 and 10.64 were used in this study. The evaporator temperatures were between 0 °C and 16 °C, the generator temperatures were between 75 °C and 120 °C and the condensing temperatures varied between 20 °C and 40 °C. For the range of parameters used, the optimal coefficient of performance (COP) is in the range 0.11 and 0.88 for evaporator temperatures between 4 °C and 16 °C. At the optimal working conditions, the COP improves with higher area ratios, lower condensing temperatures and requires increased generator temperatures. In the critical mode of operation, both the energetic and exegetic performance of the ejector are shown to decline as generator temperatures increase, evaporator temperatures reduce and as the area ratios decrease. Thermodynamic investigation using the exergy analysis method indicates that most of the exergetic losses come from the ejector (46-56%) followed by the condenser (18-29%), the generator (21-26%), the evaporator (0.8-3%), and the throttle valve (1- 1.6%), with the pump having a very small contribution. Moreover, correlations for the optimal generator and optimal COP were derived and presented. Keywords: Coefficient of performance, Critical mode, Ejector refrigeration system, Ejector loss coefficients, Exergetic performance, Hydroflouroolefins
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".