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Record W3039468098 · doi:10.3795/ksme-b.2020.44.7.415

Numerical Analysis of Active Refrigeration Performance in Thermoelectric Device Integrated with Naval Vessel Radar System

2020· article· en· W3039468098 on OpenAlexaff
Sung-Whan Yim, Dong-Kyun Lee, Heung-Tae Kim, Young-Eun Ra, Hoon Kim, Gimin Park, Woochul Kim

Bibliographic record

VenueTransactions of the Korean Society of Mechanical Engineers B · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsRefrigerationThermoelectric effectRadarMarine engineeringMaterials scienceNuclear engineeringMechanical engineeringComputer scienceEnvironmental scienceThermodynamicsTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

함정에 탑재되는 레이더 안테나 시스템은 고밀도 발열량을 지닌 열원을 포함함으로써 집중적인 냉각이 요구된다. 열원의 냉각뿐만 아니라 열원 간의 온도 균일성도 요구되기 때문에 능동적인 냉각이 가능한 열전 냉각 소자를 이용하여 온도 균일성을 이룰 수 있는 시스템의 수치 해석에 대한 연구를 진행하였다. 열전 냉각 소자는 흘려주는 전류 및 설치 면적에 따라 열원의 구체적이고 능동적인 냉각이 가능해진다. 본 논문에서는 전류 및 전력에 따른 열전 소자의 냉각 성능에 대한 결과를 도출해 내였으며 열전 소자 설치 면적에 따른 열원의 냉각량 및 온도의 균일성에 대해 해석하였다.

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 score0.009
Threshold uncertainty score0.018

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.180
Teacher spread0.172 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Korean Society of Mechanical Engineers BSame topicArctic and Antarctic ice dynamicsFrench-language works237,207