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Record W4297856916 · doi:10.1117/12.2638920

Numerical and experimental investigation on a two-stage reentry turbine

2022· article· en· W4297856916 on OpenAlexaboutno aff
Fengqi Zhu, Xiancheng Song, Shumin Zhang, Zhenjiang Li, Liguo Hu

Bibliographic record

VenueInternational Conference on Mechanical Design and Simulation (MDS 2022) · 2022
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
Fundersnot available
KeywordsTurbineReentryStatorTorquePower (physics)Aerospace engineeringMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A reentry turbine is a multi-stage turbine with only one disk, and the medium is re-introduced into the turbine cavity to do work. The reentry turbine is suitable for partial admission, which has the characteristics of small volume and high output power. This paper propose a two-stage reentry turbine of 90-millimeter-mean-diameter, and the stator is replaced by the reentry turbine pipe and Laval nozzles that change the direction and accelerate the medium. Numerical simulation indicates that the reentry turbine can maintain high efficiency; besides, the maximum torque and tangential force on a single blade of the reentry turbine are less than that of the one-stage turbine under the same conditions. The CFD calculation of the two-stage reentry turbine promised 146.7 kW output power, whereas the experiments confirmed 137 kW output power, and the simulation error is less than 7.1%. The output power of the reentry turbine is increased by 13.2% compared to the one-stage turbine. The reentry turbine can achieve high specific power with a compact structure at the condition of the increased total to static pressure radio and a small flow rate.

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 categoriesInsufficient payload (model declined to judge)
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 score0.445
Threshold uncertainty score1.000

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 head0.057
GPT teacher head0.298
Teacher spread0.241 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Conference on Mechanical Design and Simulation (MDS 2022)Same topicAerosol Filtration and Electrostatic PrecipitationFrench-language works237,207