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Record W2051068993 · doi:10.1115/gt2005-68262

CFD Analysis of a 15 Stage Axial Compressor: Part II — Results

2005· article· en· W2051068993 on OpenAlexaff
T. Belamri, Paul Galpin, André Braune, Christian Cornelius

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsGas compressorAxial compressorComputational fluid dynamicsFlow (mathematics)ComputationMechanicsCentrifugal compressorTransient (computer programming)Mass flowMechanical engineeringEngineeringComputer scienceSimulationPhysicsAlgorithm

Abstract

fetched live from OpenAlex

The flow field of a 15 stage axial compressor is analyzed using a 3-D Navier-Stokes CFD tool. The compressor under investigation is a prototype engine, first compressor version before optimization of the Siemens V84.3A family. The paper describes steady state and transient flow simulations of the entire 15 stages compressor in one computation (not piece by piece). The simulation includes tip gaps, mass bleeds, hub leakage flows, and ranges from single passage to full 360 degrees analysis. The work is divided into two companion papers. The second paper, “CFD Analysis of a 15 Stage Axial Compressor Part II: Results” describes the application of the methods in Part I to the entire 15 stage compressor (Belamri et al, 2005). The flow in the compressor is modeled first with one blade passage per component (periodicity assumed, an interface pitch change model employed). Steady state and transient models are compared. In a second series of computations, all blade passages in 360 degrees are modeled, (no periodicity or pitch change assumptions required), for portions of the compressor. The various simulation approaches are compared to each other, and to experimental data. Good agreement between predictions and experimental results, both in the details of the flow field and the integral prediction of operating range of the compressor, were found.

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: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.612

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)0.0010.000

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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

Citations20
Published2005
Admission routes1
Has abstractyes

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