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Record W2134063354 · doi:10.1115/1.2979010

Design Principles and Measured Performance of Multistage Radial Flow Microturbomachinery at Low Reynolds Numbers

2008· article· en· W2134063354 on OpenAlexaff
Chang‐Gu Lee, Selin ARSLAN, Luc G. Fréchette

Bibliographic record

VenueJournal of Fluids Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversité de Sherbrooke
FundersNational Science Foundation
KeywordsMicroscale chemistryTurbomachineryAerodynamicsComputational fluid dynamicsMechanical engineeringRotor (electric)TurbineReynolds numberAdiabatic processMicrofabricationRam air turbineMechanicsMaterials scienceSizingEngineeringPhysicsMathematicsTurbulenceThermodynamics

Abstract

fetched live from OpenAlex

This paper introduces and experimentally demonstrates the design concept of multistage microturbomachinery, which is fabricated using silicon microfabrication technology. The design process for multistage microscale turbomachinery based on meanline analysis is presented, along with computational fluid dynamics predictions of the key aerodynamic performance parameters required in this design process. This modeling was compared with a microturbine device with a 4 mm diameter rotor and 100 μm chord blades, based on microelectromechanical system technology, which was spun to 330,000 rpm and produced 0.38 W of mechanical power. Modeling suggests a turbine adiabatic efficiency of 35% and Re=266 at the maximum speed. The pressure distribution across the blade rows was measured and showed close agreement with the calculation results. Using the model, the microturbine is predicted to produce 3.2 W with an adiabatic efficiency of 63% at a rotor speed of 1.1×106 rpm.

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 score0.205
Threshold uncertainty score0.926

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 head0.011
GPT teacher head0.176
Teacher spread0.165 · 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

Citations8
Published2008
Admission routes1
Has abstractyes

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