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Record W3209719453

Evaporative Spray Cooling of Hot Air Flow from a Round Nozzle: Experiments and CFD

2020· dissertation· en· W3209719453 on OpenAlexfundaboutno aff
Alexander Wadey

Bibliographic record

VenueQSpace (Queen's University Library) · 2020
Typedissertation
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaQueen's University
KeywordsEvaporative coolerNozzleComputational fluid dynamicsEnvironmental scienceAirflowMechanicsMechanical engineeringNuclear engineeringMaterials scienceEngineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

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].
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\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).
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\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.
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\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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.194
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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