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Record W4283732722 · doi:10.1038/s41598-022-15026-8

Mitigation of jet cross-flow induced vibrations using an innovative biomimetic nozzle design inspired by shark gill geometry

2022· article· en· W4283732722 on OpenAlexafffund
Ibrahim Gad-el-Hak, Njuki Mureithi

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsPolytechnique Montréal
FundersFramatomeNatural Sciences and Engineering Research Council of Canada
KeywordsNozzleBaffleJet (fluid)Mixing (physics)MechanicsFlow (mathematics)CoolantMaterials scienceMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Shark gill slits enable sharks to eject the water after the oxygen has been removed in ram ventilation. The reduced effect of jet flow from the gill slits gives sharks smooth maneuverability. A biomimetic "shark nozzle" is proposed to improve mixing between the jet flow and surrounding fluid. Jet flow systems are an essential component of many industrial applications. The key characteristic of jet flow is the mixing process that occurs between two fluid streams to allow heat and/or mass transfer between them. Many industrial and propulsion devices that use jet flows need rapid mixing for effective and environmentally friendly operation. Fuel-injection systems, chemical reactors, and heating and air conditioning systems are examples of devices where a mixing process takes place. Recently, jet flow plays an important role in design and operation of specialized nuclear pressurized water reactors (PWRs). The loss-of-coolant accident (LOCA) holes and slots machined in the core periphery baffle plates are designed to mitigate the effects of a severe LOCA event. However, in normal operation, the holes are a source of a jet flow that can induced vibrations in the fuel assemblies near the baffle before being mixed with the surrounding fluid. This may cause wear and fretting in fuel rods with their supports. The ultimate solution to prevent the fuel assembly vibrations from LOCA hole jetting in a reactor is enhancing mixing of a jet flow with ambient flow in order to rapidly reduce jet momentum. This work proposes a new shark-inspired nozzle design that exploits the observed high efficiency capacity of shark gill slits. Tests are conducted to evaluate the performance of the new design. The obtained results show that the shark-inspired biomimetic nozzle has a greater effect on the rod bundle vibration, and the critical velocity at which the unstable vibration occurs in the rod bundle is delayed by 20% using the biomimetic nozzle. In addition to delaying instability, a vibration amplitude reduction of 85% was obtained by using the proposed shark-inspired nozzle instead of the circular nozzle.

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)0.000
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
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0010.000
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 head0.027
GPT teacher head0.264
Teacher spread0.237 · 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

Citations16
Published2022
Admission routes2
Has abstractyes

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