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Record W3201556454 · doi:10.1063/5.0059439

Near-field relaxation subsequent to the onset of oblique detonations with a two-step kinetic model

2021· article· en· W3201556454 on OpenAlexafffund
Honghui Teng, Hoi Dick Ng, Pengfei Yang, Kuanliang Wang

Bibliographic record

VenuePhysics of Fluids · 2021
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsConcordia University
FundersHigher Education Discipline Innovation ProjectNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsPhysicsDetonationStreamlines, streaklines, and pathlinesMechanicsKinetic energyFlow (mathematics)Euler equationsClassical mechanicsOblique caseWork (physics)Field (mathematics)Relaxation (psychology)Thermodynamics

Abstract

fetched live from OpenAlex

Initiation of an oblique detonation wave (ODW) results in a near-field region of curved detonation wave surface, which cannot be predicted by the detonation polar theory and lacks in-depth work on its features. In this study, Euler equations coupled with a two-step kinetic model are used to simulate ODW dynamics, and then the flow structures are analyzed by examining the asymptotic decay of local surface angle. The flow/reaction coupling is quantified by a non-dimensional Damköhler number Das that is defined as the ratio of the characteristic flow and chemical reaction length along streamlines. The results demonstrate a spectrum of local strong solutions forms, which always happens when the ODW transition pattern is abrupt, but the strong solutions deviate from the isolated strong solution predicted by the polar theory. Furthermore, the abrupt transition leads to a strong peak of Das, while the smooth one leads to a bump. Various simulated cases indicate that the transition pattern becomes abrupt and the local strong solution arises when the maximum Das reaches a critical range.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 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

Citations17
Published2021
Admission routes2
Has abstractyes

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