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Record W7011451245

Medium-scale fire experiments of commercial premises

2005· article· en· W7011451245 on OpenAlexfundvenueaboutno aff

Bibliographic record

VenueNPARC · 2005
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaPublic Works and Government Services CanadaFPInnovations
KeywordsFire testSmokeWork (physics)Fire safetyFire performanceNatural rubber
DOInot available

Abstract

fetched live from OpenAlex

This paper presents and discusses the results of a fire load survey and of a set of medium-scale fire experiments, which were jointly conducted by Carleton University and the National Research Council of Canada (NRC) to determine the burning characteristics of combustibles in commercial premises. The experiments were conducted in an ISO 9705 compatible dimensions and the fire load density used in the experiments ranged from 661 MJ/m2 to 4,900 MJ/m2. The long-term objective of this work is to develop design fires for commercial buildings. The combustibles present in the buildings were determined through a fire load survey of 168 commercial premises that was conducted in 2003 in the Canadian cities of Ottawa and Gatineau. The products in the shops included clothing, footwear, toys, computer equipment, books, foodstuff, alcohol, pharmaceuticals, arts and crafts supplies, and photographic and hairdressing products.The results from the tests reveal interesting and varied burning characteristics of the fuel packages simulating the fuel loads found in the different shops. Fuel packages consisting of high plastic, rubber and edible-oil content attained high peak heat release rates (1,300 to 1,950 KW) and exhibited fast fire growth and significant smoke production (0.96 to 2.74 OD/m). The paper also presents the detailed results, including a test log, of a fire test with a fuel package simulating a fast food shop. The results show that the fire reached a peak heat release rate of about 1562 kW at 6.5 minutes from ignition, and a peak gas temperature of 735 °C in the hot layer.

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 categoriesnone
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 score0.591
Threshold uncertainty score0.652

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.259
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2005
Admission routes3
Has abstractyes

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