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Record W4388573579 · doi:10.18280/i2m.220503

Investigating Fluid Flow Regimes: A Novel Design and Implementation of Bernoulli’s Apparatus

2023· article· en· W4388573579 on OpenAlexvenueno aff
Bernard A. Adaramola, Joseph F. Kayode, Sunday A. Afolalu, Oluwasina L. Rominiyi, Imhade P. Okokpujie, Omolayo M. Ikumapayi

Bibliographic record

VenueInstrumentation Mesure Métrologie · 2023
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsBernoulli's principleFlow (mathematics)Fluid dynamicsMechanicsComputer scienceEnvironmental sciencePhysicsEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

The Bernoulli's apparatus, a pivotal tool for exploring fluid flow characteristics within piping architecture, has been designed with an emphasis on usability, reliability, affordability, and material accessibility.This device, encompassing Venturimeters, pressure gauges, pipes, and capillary tubes, was fabricated and assembled within the central Engineering workshop at ABUAD.The apparatus was designed to enable the utilization of pressure gauges for the measurement of pressure head within pipes.Experimental procedures entailed the examination of varied water flow rates, with pressure head and volume measurements taken over 20-second intervals.The Reynolds's number was calculated, utilizing the viscosity and density of water, alongside the pipe diameter and velocity, to classify the fluid flow as either laminar, transitional, or turbulent.Results indicated an escalation in Reynolds number concurrent with the flow rate.For each discharge, Reynolds's numbers and flow categorizations were determined.The initial discharge yielded a Reynolds number approximating 3819, signifying transitional flow.Subsequent discharges demonstrated Reynolds numbers of approximately 5347, 7129, 8912, 10439, and 12371, respectively, indicative of turbulent flow.Turbulent flows are characterized by high velocities, unpredictable variations in flow magnitude and direction, and erratic alterations in pressure.

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)0.001
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 score0.108
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.055
GPT teacher head0.331
Teacher spread0.277 · 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
Published2023
Admission routes1
Has abstractyes

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