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Record W2109095024 · doi:10.1002/cjce.21669

Study on flow fields in a bioreactor with perforated blades

2012· article· en· W2109095024 on OpenAlexvenueaboutno aff
Bie Xiaomei, Fengxia Lv, Chong Zhang, Lu Zhaoxin

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceParticle image velocimetryMechanicsFlow (mathematics)Fluid dynamicsComputational fluid dynamicsImpellerAnisotropyMechanical engineeringMaterials sciencePhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

Abstract Flow fields of a gas–liquid fluid in a bioreactor with perforated blades were evaluated with the computational fluid dynamics and particle image velocimetry (PIV). The flow pattern of the fluid was the complex turbulence, and the fluid had preferable flow fields for fermentations. Using a rotating coordinate system and a sliding mesh method, a mesh of 24 × 16 × 80 ( X × Y × Z ) was selected due to its high accuracy and appropriate workload. The numerical results of the two‐phase flow model agreed well with the experimental results of the PIV, such as flow field characteristics and data curves. The RNG k – ε model was adopted, which could precisely simulate anisotropic flow fields around higher‐speed blades. Whole deviations of X ‐, Y ‐ and Z ‐direction velocities ranged only from 5.4% to 10.5%, and continuous turbulence models could effectively simulate transfer procedures of the fluid. Because of its low cost, simplicity and easy of scale‐up, the bioreactor with perforated blades and its models mechanism of fluid microelements are expected to be efficient for its industrial amplification and application in food industry. © 2012 Canadian Society for Chemical Engineering

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 score0.047
Threshold uncertainty score0.292

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 head0.175
Teacher spread0.167 · 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

Citations2
Published2012
Admission routes2
Has abstractyes

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