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Record W2153058298 · doi:10.1098/rspa.2007.1821

Ignition and combustion of low-exothermicity porous materials by a local hotspot

2007· article· en· W2153058298 on OpenAlexaff
A.A. Shah, J. Brindley, Andy C. McIntosh, J. Griffiths

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2007
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCombustionIgnition systemConvectionPorosityMechanicsPorous mediumMaterials scienceHotspot (geology)Spontaneous combustionNatural convectionThermodynamicsComposite materialChemistryPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

We present numerical investigations of a spherically symmetric model for the ignition and subsequent combustion of low-exothermicity porous materials exposed to a constant, continuous heat source. We account simultaneously for oxidant, the gas-dynamic processes, including a gaseous product of reaction, and a solid product that is allowed to assume different physical properties from the solid reactant. For external conditions that are typical of natural convection, the model exhibits striking novel behaviour, including the possibility of a potentially dangerous high-temperature ‘burnout’ at the external surface of the material, which triggers a reverse combustion wave propagating from the outer surface of the solid towards the heat source. This phenomenology is controlled largely by the diffusion of oxygen entering the system. We identify the effects that convection and product properties have on combustion of the solid, particularly on the formation of a reverse wave. Applications of the approach to specific problems are discussed and future work is outlined.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.289

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)0.0000.000

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 head0.006
GPT teacher head0.198
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 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

Citations6
Published2007
Admission routes1
Has abstractyes

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