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Record W3158889732 · doi:10.3390/fluids6050170

An Analytical Solution for Unsteady Laminar Flow in Tubes with a Tapered Wall Thickness

2021· article· en· W3158889732 on OpenAlexaff
Travis Wiens, Elnaz Etminan

Bibliographic record

VenueFluids · 2021
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWater hammerLaminar flowMechanicsPipeline (software)Transient (computer programming)Tube (container)Flow (mathematics)Pipe flowComputational fluid dynamicsFrequency domainComputer sciencePhysicsMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Transient fluid flows through tubes are critical in such topics as water hammer, ram pumps and pipeline dynamics. While analytical solutions exist in the literature for simple geometries such as tapered and non-tapered tube diameters, one area that is lacking is the case where the wave speed changes along the length. An example of this is a flexible pipe with a tapered wall thickness. In order to calculate the transient pressure response of such a system, this previously required a computationally expensive gridded method of characteristics (MOC) solution. This paper describes an analytical solution to the dynamic laminar flow of liquid in a tube where the wave speed varies along its length. This frequency-domain solution includes frequency-dependent friction effects. A comparison to a method of characteristics (MOC) solution is used to verify the solution. The paper also discusses some numerical issues and provides an approximate method that can be used for high-frequency calculations where limited numerical precision can cause errors. Finally, a preliminary comparison of the computational performance is presented, in which the new method is an order of magnitude faster to calculate than an MOC solution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations7
Published2021
Admission routes1
Has abstractyes

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