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Record W4206015310 · doi:10.2172/1821536

Fuels Characterization for National Research Council Canada 2-m Pool Fire Test Series

2021· report· en· W4206015310 on OpenAlexaboutno aff
David Lord, Joseph Hogge, Raymond Allen

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
Fundersnot available
KeywordsHeptaneCombustionAsphaltVapor pressureHydrocarbonMineralogyChemistryEnvironmental scienceWaste managementAnalytical Chemistry (journal)Materials scienceEnvironmental chemistryComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

This report provides a detailed analysis of the physical and chemical properties of three liquid hydrocarbon fuels: heptane, Bakken crude, and a diluted bitumen, that were subsequently tested in a series of 2-m pool fire experiments at Sandia National Laboratories for the National Research Council Canada. Properties such as relative density, vapor pressure (VPCR x ), composition, and heat of combustion were evaluated. The heptane analysis, with relative density = 0.69 (at 15C), confirmed that the material tested was consistent with high-purity (>99%) n-heptane. The Bakken crude, with a relative density = 0.81 (at 15C), exhibited a vapor pressure by VPCR 0.2 (37.8C) in the range 120-157 kPa. The dilbit, with a relative density = 0.92 (at 15C) exhibited a vapor pressure by VPCR 0.2 (37.8C) in the range 85-98 kPa. Solids remaining in the test pans after the pool fires were also collected and weighed. No detectable solids were left after the heptane burns. In contrast, the crude oils left some brittle, black solid residue. On average, dilbit pool fires left about 40 more residue by mass than Bakken pool fires for equivalent mass of fuel feed.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.718
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
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 integrity0.0000.001
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 head0.120
GPT teacher head0.314
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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