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Record W2329205951 · doi:10.1115/fedsm2005-77084

Comparison of Computational Results Obtained From a VOF Cavitation Model With Experimental Investigations of Three Inducers: Part I — Experimental Investigations; Part II — Numerical Analysis

2005· article· en· W2329205951 on OpenAlexaff
Imene Mejri, Farid Bakir, R. Rey, T. Belamri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsAnsys (Canada)
Fundersnot available
KeywordsCavitationVolume of fluid methodMechanicsDiscretizationComputational fluid dynamicsInducerShroudComputer simulationFlow (mathematics)Materials scienceMechanical engineeringPhysicsEngineeringChemistryMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

The paper presents full 3D numerical simulations and experimental investigations of the cavitating flow through three axial inducers. These inducers are identified by the blades leading edge angle at the periphery β1T = 8°, 10°, 13° and are thus noted as Inducer 8°, Inducer 10° and Inducer 13°. They have the same tip and hub diameters. The numerical and experimental investigations were carried out at the LEMFI-Paris laboratory. This enabled us to explain the cavitating operation for off-design conditions. In Part I of this paper we describe the design methodology adopted for the inducers and which is deduced from literature and in house experience. Then the main experimental results are presented for the studied inducers at a range of flow rates and cavitation numbers concerning: • The overall performances: pressure head coefficient and efficiency versus several flow rates. • Critical cavitation number (5% and 15% of drop) versus the flow rate. In Part II of this paper, a review of the cavitating regime modeling and the cavitation VOF model used for this paper’s calculations is firstly presented. The numerical approach is based on a combination of the VOF technique with a truncated version of the Rayleigh-Plesset model predicting the complicated growth and collapse processes of bubbles. The cavitation model also features a control volume finite element discretization and a solution methodology which implicitly couples the continuity and momentum equations together. The numerical results of Part II concern: • The overall performances. • The numerically investigated water vapor volume fraction distributions and other CFD results, which enable us to explain the cavitating behavior for these inducers. • The location and sizes of the blade cavity and backflow vortex. Finally, the comparisons between experimental and simulated results on the overall performances, cavities sizes and cavities location are discussed. A good agreement between experimental and predicted results was found for a range of flow rates. The head breakdown in the simulations started at a different cavitation coefficient than that in the experiment.

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 categoriesMeta-epidemiology (narrow)
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 score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.051
GPT teacher head0.296
Teacher spread0.245 · 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

Citations9
Published2005
Admission routes1
Has abstractyes

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