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Record W3165734766 · doi:10.5539/esr.v10n2p23

Ionic Strength and Drag Reduction of Polymers in Straight Pipes – An Experimental Investigation

2021· article· en· W3165734766 on OpenAlexvenueno aff
Ahmed H. Kamel

Bibliographic record

VenueEarth Science Research · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIonic strengthDragMaterials sciencePolymerReynolds numberIonic bondingSalt (chemistry)ChemistryThermodynamicsComposite materialAqueous solutionPhysicsIonOrganic chemistryTurbulence

Abstract

fetched live from OpenAlex

Previous work has tied the drag reduction properties of polymer solutions to type and concentration of salts, rather than its ionic strength, although it is a more extensive parameter to investigate the effects of salt contents on fluids behavior. The current study aims at investigating the relationship between ionic strength and drag reduction characteristics of polymer solutions when flowing in straight tubing. Nalco ASP-700 and ASP-820, two common anionic AMPS copolymers, are examined with various salts (2% KCl, 4% KCl, and synthetic seawater). Flow tests were conducted using a small-scale flow loop that includes a straight tubing with an outside diameter of 1.27 cm and a length of 4.57 m. It has been found that drag reduction performance of polymer solutions is well correlated with ionic strength, rather than salt type and/or concentration. With high ionic strength, lower drag reduction is noticed despite of the reduced salt concentration. Nevertheless, at higher Reynolds number, the effects of ionic strength minimizes. Both polymer solutions exhibit effective drag reduction characteristics and their behavior is greatly affected by polymer type, shear rate, and salt content. Correlations, with acceptable confidence level, between drag reduction ratio and solutions ionic strength are proposed. The correlations are strongly recommended to investigate the effects of salt types and/or concentrations, represented by its ionic strength on drag reduction behavior of polymer solutions in straight tubing.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.038
GPT teacher head0.343
Teacher spread0.304 · 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 designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

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