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Record W2898593896 · doi:10.1115/fedsm2018-83062

Investigation of Unsteady Flow in a Submersible Tubular Pumping System

2018· article· en· W2898593896 on OpenAlexaff
Yan Jin, Hongcheng Chen, David S.‐K. Ting, Jacqueline Stagner, Junxin Wu, Chao Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsImpellerMechanicsFlow (mathematics)StatorRotor (electric)TurbulenceComputational fluid dynamicsTurbomachineryMechanical engineeringPhysicsEngineeringMarine engineering

Abstract

fetched live from OpenAlex

To better understand the workings of submersible tubular pumping system and to enable future improvements, the pressure fluctuation and unsteady flow characteristics due to the complex rotor-stator interactions need to be properly delineated. High-frequency pressure measurements coupled with CFD simulations have been invoked in this study to elucidate the unsteady flow in different components of a submersible tubular pumping system at different discharges. The focus is on the impeller and guide vane, where the unsteady interaction is the strongest. The pressure pulsation distributions of different characteristic cross sections such as impeller exit, middle of guide vane, and exit of guide vane were quantified. In addition, the flow characteristics and the turbulent kinetic energy inside the impeller, guide vane, and bulb unit were obtained at the different time steps. The results show that the pressure pulsation frequency obtained by simulation was in agreement with the experimental results, including the critical points around the impeller and the guide vanes. The complementary two-prong approach is thus proven to be a powerful duo in researching and advancing a convoluted pumping system.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.301

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 head0.014
GPT teacher head0.193
Teacher spread0.180 · 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 designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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