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Record W2257858732 · doi:10.1520/stp159620150081

Oxygen Partial Pressure and Oxygen Concentration Flammability: Can They Be Correlated?

2016· book-chapter· en· W2257858732 on OpenAlexaff
Susana Harper, Alfredo Juarez, Horacio Perez, David B. Hirsch, Harold D. Beeson

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsFlammabilityOxygenPartial pressureOxygen pressureFlammability limitMaterials scienceChemistryComposite materialCombustionOrganic chemistry

Abstract

fetched live from OpenAlex

NASA possesses a large quantity of flammability data performed in International Space Station (ISS) airlock (30 % Oxygen 526 mmHg) and ISS cabin (24.1 % Oxygen 760 mmHg) conditions. As new programs develop, other oxygen and pressure conditions emerge. In an effort to apply existing data, the question arises: Do equivalent oxygen partial pressures perform similarly with respect to flammability? This paper evaluates how material flammability performance is impacted from both the maximum oxygen concentration (MOC) and maximum total pressures (MTP) perspectives. From these studies, oxygen partial pressures can be compared for both the MOC and MTP methods to determine the role of partial pressure in material flammability. This evaluation also assesses the influence of other variables on flammability performance. The findings presented in this paper suggest flammability is more dependent on oxygen concentration than equivalent partial pressure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2016
Admission routes1
Has abstractyes

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