Current Advances in Ejector Modeling, Experimentation and Applications for Refrigeration and Heat Pumps. Part 1: Single-Phase Ejectors
Bibliographic record
Abstract
Ejectors used in refrigeration systems as entrainment and compression components or expanders, alone or in combination with other equipment devices, have gained renewed interest from the scientific community as a means of low temperature heat recovery and more efficient energy use. This paper summarizes the main findings and trends, in the area of heat-driven ejectors and ejector-based machines, using low boiling point working fluids, which were reported in the literature for a number of promising applications. An overall view of such systems is provided by discussing the ejector physics principles, as well as a review of the main developments in ejectors over the last few years. Recent achievements on thermally activated ejectors for single-phase compressible fluids are the main focus in this part of the review. Aspects related to their design, operation, theoretical and experimental approaches employed, analysis of the complex interacting phenomena taking place within the device, and performance are highlighted. Conventional and improved ejector refrigeration cycles are discussed. Some cycles of interest employing ejectors alone or boosted combinations are presented and their potential applications are indicated.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".