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Record W2388655592

Simulation Study on Atomization Process of Pulsed Anti-riots Water Cannon with Laval Nozzle

2013· article· en· W2388655592 on OpenAlexaboutno aff
Yongli Li

Bibliographic record

VenueFire Control and Command Control · 2013
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Launch and Propulsion Technology
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleEmulationEngineeringMechanical engineeringJet (fluid)Process (computing)Water jetMechanicsSimulationMarine engineeringAerospace engineeringPhysicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

In this paper,we study the anti-riots water cannon optimal control problem.The high-pressure gas is as the driving force of anti-riots water cannon.Jet nozzle is the emission element of anti-riots water cannon.The laval nozzle are designed according to the jet structure of the police pulsed anti-riots water cannon.Coupling the VOF with LES model,we build the mathematic model and physical model of the nozzle,and use the OpenFOAM software to emulation the area near the nozzle.Through the research it was found that the laval nozzle can achieve good result on atomization effect and cannon-shot.At the same time,through the simulation and analysis of the area near laval nozzle from the sides of atomization form and angle,distribution of velocity.We established that field angle between 15° and 18° is more reasonable,as providing a reference for farther optimize of pulsed water cannon.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.003
GPT teacher head0.181
Teacher spread0.179 · 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 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
Published2013
Admission routes1
Has abstractyes

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