Ice slurry production via opposed-jets spray: An experimental and theoretical study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The opposed nozzle impinging method is a novel developed technology for ice slurry preparation, which has more advantages than the traditional method, such as increasing the effective heat transfer contact area, significantly reducing ice plugging, and improving the heat transfer efficiency. The injection angle, flow rate and injector distance are investigated experimentally in this work due to their great influence on system performance. Consequently, the optimum parameters and the functional relationship between the system performance parameters and the key operating parameters are obtained. It is shown that increasing the spray angle of the gas and liquid streams increases the ice packing fraction (IPF) by up to 6.09 %. The increase in the IPF growth rate is 2.974 times greater when the gas spray angle is changed from 45° to 105°, compared to a similar change in the liquid nozzle angle. The cold energy utilization rate of the ice slurry generated increases by 16.02 % when the gas–liquid spray angle increases from 45° to 105°. Moreover, the order of influencing factors on the IPF and heat transfer efficiency according to orthogonal experiments from the highest to lowest is distance between nozzles, liquid nozzle flow rate, air nozzle flow rate. The optimal values for the nozzle distance, air nozzle flow rate and liquid nozzle flow rate are 8 cm, 6.4 m 3 /h, and 48L/h, respectively. Moreover, a novel mathematical model is built up to explain theoretically the influence of spray angles, fluid properties and construction parameters on ice content.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it