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Record W2326373391 · doi:10.1115/gt2006-90192

Multi-Disciplinary Design Tool for Axial Flow Turbines

2006· article· en· W2326373391 on OpenAlexaff
S. C. Kenny, Jérôme Gauthier, Xiao Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsCarleton University
Fundersnot available
KeywordsAerodynamicsComputational fluid dynamicsFinite element methodDesign toolTurbineFlow (mathematics)Computer scienceAxial compressorMechanical engineeringDesign flowEngineeringMarine engineeringStructural engineeringAerospace engineeringMechanics

Abstract

fetched live from OpenAlex

A preliminary design tool has been created to aid in the design of axial flow turbines. The design tool outputs all of the required geometry and flow conditions for the preliminary design of a single stage axial turbine. Inherent to the tool is its ability to produce performance estimates, both aerodynamically and structurally. The aerodynamic analysis is largely empirical based and makes use of the most up-to-date correlations available in the literature. The tool has been created to obtain a fast estimate of performance and a fast screening of various design variables. The design tool is also required in order to produce a geometrical input for more advanced computational fluid dynamic (CFD) and finite element method (FEM) analyses. A test case has been conducted through the design and development of two single stage turbines for a 1-MW gas turbine engine. The results of the design tool were then compared to those results obtained from extensive CFD and FEM analyses to validate the accuracy of the tool. Overall, the results showed excellent agreement both aerodynamically and structurally.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.436
Threshold uncertainty score0.334

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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
GenreMethods

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
Published2006
Admission routes1
Has abstractyes

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