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Record W2099225632 · doi:10.3801/iafss.fss.8-741

Application Of Water Mist To Extinguish Large Oil Pool Fires For Industrial Oil Cooker Protection

2005· article· en· W2099225632 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFire Safety Science · 2005
Typearticle
Languageen
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCookerMistEnvironmental scienceWaste managementEnvironmental engineeringPetroleum engineeringEngineeringMeteorologyMechanical engineering

Abstract

fetched live from OpenAlex

Large oil fires occurring in industrial oil cookers are very challenging to extinguish due to their size and the large amount of hot oil involved. This paper reports a study to use water mist for large industrial oil cooker protection. The extinguishing mechanisms of water mist and corresponding criteria required for extinguishing large pool cooking oil fires were investigated both theoretically and experimentally. Based on the extinguishing mechanisms and required criteria, two water mist systems were developed in the present work. A series of full-scale fire tests were conducted in a large industrial oil cooker mock-up. The study showed that the two water mist systems presently developed worked effectively to extinguish large cooking oil fires and prevented them from re-igniting. Their extinguishing performance was determined by the type of water mist system, discharge pressure and hood position in the oil cooker.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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