Evaporative Spray Cooling of Hot Air Flow from a Round Nozzle: Experiments and CFD
Bibliographic record
Abstract
Evaporative spray cooling is a technique that utilizes the latent heat of evaporation of a cold liquid spray to rapidly cool a hot gaseous source. During evaporation the liquid droplets are fixed at their boiling point, ensuring a large temperature differential between liquid and gas, and promoting high heat transfer rates. The application of note for this research is the infrared radiation (IR) suppression of naval vessel exhaust streams which have a distinctive radiative signature due to the hot carbon dioxide and water vapour within the exhaust. Cooling of the exhaust stream greatly reduces this signature and limits the possibility of tracking by hostile sources [1]. \n \nDespite extensive and historical use in fields such as fire suppression, the detailed mechanics of evaporative sprays are incredibly complex and predictive simulation of these flows has only been made possible with the rapid increase in computational power over the last two decades [2]. This research presents a dual approach in which results from optical measurements of a scale naval vessel exhaust system equipped with evaporative spray cooling are compared with the findings of multi-phase spray flow computational fluid dynamics (CFD). \n \nSpray flow experiments were run at the Grant Timmins research facility on the Hot Gas Wind Tunnel (HGWT), a rig capable of emulating a scale naval vessel exhaust system. With previous research focussing on direct spray measurement, an optical approach was undertaken utilizing a laser sheet to produce overall spray images and high-speed droplet imagery. In conjunction with experimentation a spray flow CFD study was constructed within the ANSYS suite of software tools. Given the complexity of real-world spray mechanics, simplified models form the bulk of the droplet-gas interaction within CFD and ensuring these models perform well together forms the crux of these simulations. \n \nThe CFD results produced compare well with droplet velocity measurements, but spray spread and evaporation rates do not match experiment. Despite this, it is likely that a robust predictive CFD methodology may yet be created in the same software suite given further inquiry.
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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 | 0.001 |
| 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".