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Record W2898291708 · doi:10.1115/fedsm2018-83519

Turbulent Flow Characteristics Over Offset Wall Confined Columns in a Channel at Low Reynolds Numbers

2018· article· en· W2898291708 on OpenAlexaff
Kira Toxopeus, Kamran Siddiqui

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsReynolds numberMechanicsTurbulenceHeat transferOpen-channel flowMaterials scienceVortexHeat transfer enhancementParticle image velocimetryWorking fluidPhysics

Abstract

fetched live from OpenAlex

The current study is focused on the flow through offset, wall confined vertical inserts in a channel. The columns are intended to act as the thermal storage media, which continuously exchange heat with the channel fluid to regulate it thermally. These columns could, for example, be filled with a phase change material (PCM) for passive thermal regulation, or have hot or cold fluid pumped through them for active thermal regulation. The current study has two parts: (1) the flow characterization without heat transfer, and (2) flow characterization during thermal exchange with a PCM used for regulation of bulk fluid temperature. The work presented here is focused only on the first part of the study. The experiments were conducted in a narrow channel, with water as the working fluid. Two geometries of the vertical columns (circular and square) and two offset lengths were considered. For each configuration, experiments were conducted at Reynolds numbers of 20, 50 and 90 (based of the column’s characteristic length). Particle image velocimetry was used to measure the two-dimensional velocity field in a horizontal plane at multiple regions of interest along the length of the channel to characterize the flow passing over columns. The results indicate vortex shedding at the two higher Reynolds numbers. The generation, magnitude and decay rate of turbulent energy is shown to have an offset dependency at Re = 90, but a column shape dependency at Re = 50. The mean flow has a shape dependency due to the difference in separation point over the square and circular columns.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
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)0.0030.001

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 head0.009
GPT teacher head0.203
Teacher spread0.195 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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