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Record W1991324731 · doi:10.1002/kin.20157

Experimental and kinetic study of shock initiated ignition in homogeneous methane–hydrogen–air mixtures at engine‐relevant conditions

2006· article· en· W1991324731 on OpenAlexaff
Jian Huang, W. Kendal Bushe, Philip G. Hill, Sandeep Munshi

Bibliographic record

VenueInternational Journal of Chemical Kinetics · 2006
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryHydrogenShock tubeMethaneIgnition systemStoichiometryBranching (polymer chemistry)ThermodynamicsMole fractionAnalytical Chemistry (journal)Organic chemistryPhysical chemistryShock wave

Abstract

fetched live from OpenAlex

Abstract The ignition delay time of two stoichiometric methane/hydrogen/air mixtures has been measured in a shock tube facility at pressures from 16 to 40 atm and temperatures from 1000 to 1300 K. Overall, the observed reduction in ignition delay with some methane replaced by hydrogen is relatively small given the large concentration of hydrogen involved in the current study. With a high hydrogen mole fraction (35% of the total fuel), a reduction of the ignition‐promoting effect was observed with reduced temperature. A detailed chemical kinetic mechanism was used to simulate ignitions of test mixtures behind reflected shocks. An analysis of the mechanism indicates that at higher temperatures, the rapid decomposition of hydrogen molecules leads to a quick formation of H radical pools, which promote the chain branching through H + O 2 ⇌ O + OH. At lower temperatures, the branching efficiency of hydrogen is low; a weak effect of hydrogen on methane ignition could be result from the reaction between H 2 and methylperoxy CH 3 O 2 , which contributes extra H radicals to the reaction system. The effects of hydrogen also decrease with increasing pressure; this is related to the negative pressure dependence of hydrogen at the second ignition limit. © 2006 Wiley Periodicals, Inc. Int J Chem Kinet 38: 221–233, 2006

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)0.000
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.277
Teacher spread0.263 · 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

Citations87
Published2006
Admission routes1
Has abstractyes

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