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Record W4214624768 · doi:10.1115/1.4053970

A Robust Pseudo-Three-Dimensional Computational Fluid Dynamic Approach for Industrial Applications

2022· article· en· W4214624768 on OpenAlexafffund
Sichang Xu, Eugene Ryzer, G. W. Rankin

Bibliographic record

VenueJournal of Fluids Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Windsor
FundersMitacsOntario Centres of Excellence
KeywordsComputer scienceComputational fluid dynamicsFluid dynamicsSimple (philosophy)Internal flowFlow (mathematics)Mathematical optimizationMechanicsMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract Two-dimensional instead of three-dimensional computational fluid dynamic solutions of flow problems are quite often used in industry to facilitate short design turn-around times with varying degrees of success. A simple and robust approach for improving the accuracy of two-dimensional computational fluid dynamics solutions for problems involving internal flow passages in industrial applications is presented. The technique utilizes an approximation to the shearing stresses that act in the fully three-dimensional case but are ignored in the traditional two-dimensional approximation. Although the technique does not fully account for all the three-dimensional effects in such flows, it gives a reasonable estimate of the operation of devices with internal flows, even those involving transients. The usefulness and accuracy of the method are demonstrated through the application of the method to predict the performance of a supersonic fluidic oscillator for industrial design purposes. This brief provides industrial designers with a simple and robust tool for improving the accuracy of their computational fluid dynamic simulations.

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: Methods · Consensus signal: none
Teacher disagreement score0.673
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)0.0000.000

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 head0.017
GPT teacher head0.205
Teacher spread0.189 · 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
GenreMethods

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

Citations4
Published2022
Admission routes2
Has abstractyes

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