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Record W2319309147 · doi:10.2514/6.2005-3968

Detonations Structure with a Chain-Branching Model Yielding Three Explosion Limits

2005· article· en· W2319309147 on OpenAlexafffund
Zhe Liang, Luc Bauwens

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaKillam Trusts
KeywordsBranching (polymer chemistry)Chain (unit)Computer sciencePhysicsMaterials scienceAstronomyComposite material

Abstract

fetched live from OpenAlex

Hydrogen-oxygen chemistry is characterized by a chain-branching mechanism that yields three explosion limits. An appropriate detailed kinetic scheme should produce the correct chain-branching behavior, but in many circumstances, a simpler yet reasonably realistic model will be warranted. It is also easier to develop a clear understanding of the reaction zone structure using a simpler model, that includes only the key mechanisms. To that efiect, we consider a four step chain-branching scheme that exhibits an explosion behavior with three limits, very similar to hydrogen. We focus in particular on the structure of a detonation wave, using a combination between numerical simulation and analysis. Numerical simulations using the four step scheme show distinctive keystone flgures in the ∞ow fleld, close to observations in hydrogen-oxygen detonation experiments. The steady wave structure is resolved using a perturbation analysis, which clarifles the difierences between explosion and no-explosion regions and allows for an evaluation of the reaction length. The analysis assumes both high activation energy and a slow initiation. Three cases are identifled, respectively with post-shock pressure and temperature located within the explosion region, close to the explosion limit and within the no-explosion region. The induction length is shorter and the reaction rate is faster by several orders of magnitude in the explosion region.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.390

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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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 designSimulation or modeling
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 routes2
Has abstractyes

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