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Record W4392372350 · doi:10.1002/cjce.25231

Numerical simulation of inter‐stage of multistage centrifugal pump by varying number of blades

2024· article· en· W4392372350 on OpenAlexvenueno aff
D. D. Yadav, Raj Kumar Singh, Manjunath Kumarswamy

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsnot available
Fundersnot available
KeywordsImpellerCentrifugal pumpDiffuser (optics)Computer simulationStage (stratigraphy)Rotational speedComputationHead (geology)Parametric statisticsMechanical engineeringComputer scienceEngineeringMechanicsSimulationMathematicsPhysicsAlgorithm

Abstract

fetched live from OpenAlex

Abstract Numerous impellers are placed in line on the same shaft in a multistage centrifugal pump, comprising an impeller, diffuser, and return channel. The design of a two‐stage multistage centrifugal pump according to the specifications given in the literature was created using Creo Parametric software and validated by carrying out a numerical simulation of the first‐stage centrifugal pump by varying the number of blades and impeller speed and concluding that the pump with 7 blades and 1900 rpm rotation gives the best efficiency and head by comparing the obtained results to experimental ones. ANSYS Fluent 2022R1 was used for simulation. The optimal solutions from the first stage were used to analyze the second stage. It was observed that losses in the diffuser of the 1st stage and 2nd stage are almost the same, but head losses in the return passage of the 1st stage and 2nd stage have differences of 19.99%, 28.5%, and 23.59% for 5, 6, and 7 blades, respectively. The findings show that the multistage simulation could more accurately mirror the actual flow than the two‐stage simulation, but it also had more demanding computer configuration requirements. A two‐stage simulation is a good option for estimating pump performance because it balances computation time and numerical precision better.

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 score0.090
Threshold uncertainty score0.452

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 head0.008
GPT teacher head0.223
Teacher spread0.216 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicCavitation Phenomena in PumpsFrench-language works237,207