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Record W2800247317 · doi:10.1117/12.2304599

Active hull cooling system performance analysis

2018· article· en· W2800247317 on OpenAlexaff
David A. Vaitekunas, P S Aleksandrov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsHullNozzleWater coolingTransient (computer programming)Marine engineeringRange (aeronautics)Computer scienceInfraredEnvironmental scienceEngineeringMeteorologyMechanical engineeringAerospace engineeringOperating systemPhysics

Abstract

fetched live from OpenAlex

The effects of Hull Film Cooling (HFC) water-spray systems on infrared detection have already been presented by Vaitekunas and Kim ([9],[10]). This paper will further assess the impact of zonal Active Hull Cooling (AHC) water-spray systems on the infrared detection of naval ships to ensure its proper usage against a range of infrared-guided anti-ship missiles. The transient performance of such systems will also be assessed using a fully transient version of ShipIR/NTCS which includes a laminar flow water-film convection model to simulate the effects of an activated water-spray. The model can be used to analyse the performance of a proposed design, and adjust the nozzle count to meet a specific requirement. Recent efforts to validate the new model against existing experiments is also described.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.676
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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 teacher head, 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

Citations2
Published2018
Admission routes1
Has abstractyes

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