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Record W2083928876 · doi:10.1142/s0217984909018722

THE NUMERICAL SIMULATION OF FLOW AROUND EJECTION SYSTEM

2009· article· en· W2083928876 on OpenAlexaboutno aff
Dalin Zhang, Tao Wei

Bibliographic record

VenueModern Physics Letters B · 2009
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDiscretizationFinite volume methodAerodynamicsComputer scienceDomain decomposition methodsFlow (mathematics)Upwind schemeMach numberTurbulenceComputationNavier–Stokes equationsReynolds-averaged Navier–Stokes equationsApplied mathematicsMechanicsMathematicsPhysicsMathematical analysisFinite element methodAlgorithm

Abstract

fetched live from OpenAlex

Aerodynamic characteristics of an Ejection Seat System at different angles of attack are studied by the numerical method and the flow mechanisms for such flows are carefully analyzed. The governing equations are Reynolds-averaged Navier-Stokes equations which are solved by the unstructured finite volume method. Upwind Osher scheme is used for spatial discretization and five-stage Runge-Kutta scheme is applied for temporal discretization. The DES model based on S-A one equation turbulence model is adopted. Parallel computation is based on the domain decomposition method and multi-block is achieved by using METIS system. The experimental data is used to validate this method. This research is helpful to understand the aerodynamic characteristics and flow mechanisms of Ejection Seat System at different angles of attack and Mach numbers, and can provide reasonable reference for Ejection Seat System design.

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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.200
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 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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venueModern Physics Letters BSame topicVibration and Dynamic AnalysisFrench-language works237,207