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Record W3100778264

Micro Cavitation Bubbles on the Movement of an Experimental Submarine: Theory and Experiments

2016· article· en· W3100778264 on OpenAlexaff
Stefan C. Mancas, Shahrdad G. Sajjadi, Asalie Anderson, Derek Hoffman

Bibliographic record

VenueScholarly Commons (Embry–Riddle Aeronautical University) · 2016
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsTrinity College
Fundersnot available
KeywordsBuoyancyCavitationSubmarineUnderwaterNeutral buoyancyMechanicsHydrostatic equilibriumBubbleHydrostatic pressureMaterials scienceMarine engineeringEnvironmental scienceGeologyEngineeringPhysicsOceanography
DOInot available

Abstract

fetched live from OpenAlex

To understand the nature of movement of submarine, micro cavitation bubbles were systematically diffused around the exterior of a test body (tube) fully submerged in a water tank. The primary purpose was to assess the feasibility of applying micro cavitation as a means of depth control for underwater vehicles, mainly but not limited to submarines. Ideally, the results would indicate the use of micro cavitation as a more efficient alternative to underwater vehicle depth control than the conventional ballast tank method. The current approach utilizes the Archimedes' principle of buoyancy to alter the density of the object affected, making it less than, or greater than the density of the surrounding fluid. However, this process is too slow for underwater vehicles to react to sudden obstacles inherent in their environment. Rather than altering its internal density, this experiment aimed to investigate the response that would occur if the density of its environment is manipulated instead. In theory, and in a hydrostatic fluid, diffusing micro air bubbles from the top surface of the submarine would dilute the column of water above it with air cavities, thus lowering the density of the water. The resulting pressure differential would then cause the submarine to gain buoyancy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.217
Teacher spread0.194 · 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
Published2016
Admission routes1
Has abstractyes

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