Supersonic Ejectors in Hydrogen Refueling Stations and Fuel Cell Systems: A Review
Bibliographic record
Abstract
Hydrogen fueling stations are becoming more widespread due to the global shift toward net zero emissions. This drives the need to improve their efficiency and reduce their energy consumption. Supersonic ejectors offer a passive alternative to traditional mechanical valves and compressors. Their integration into hydrogen fueling stations can lower compression costs and reduce refueling energy; however, the efficiency significantly drops when operating within the subcritical region resulting in an unstable system or reverse flow. Despite the advancements in ejector system analysis through numerical modeling and computational fluid dynamics (CFD), the performance limitations highlight the need for experimental validation under real-world conditions. Evaluating safety risks, adaptability to variable flow and system fluctuations is needed through an ejector system set up with instrumentation and monitoring. This review explores ejector research developments with a focus on parameters affecting efficiency such as the entrainment ratio, compression ratio, and coefficient of performance. The important role of supersonic ejectors for hydrogen recirculation in Fuel Cell systems is also discussed. Future research should focus on addressing scalability, geometry limitations, control strategies, and experimental validation to enhance ejectors’ potential to be incorporated into hydrogen fueling applications and enhanced performance in Fuel Cell applications.
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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".