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Design of a Cylindrical Jet Impingement Cooling System for High-Power Common-Mode Choke in Aerospace Applications

2024· article· en· W4396593675 on OpenAlexafffund
Sam Hemming, Di Wang, Mohamed Hefny, Sreejth Chakkalakkal, Giorgio Pietrini, Armen Baronian, Piranavan Suntharalingam, Mikhail Goykhman, Ali Emadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsMcMaster University
FundersMitacs
KeywordsChokeAerospaceJet (fluid)Aerospace engineeringMode (computer interface)Power (physics)Water coolingMaterials scienceMechanical engineeringMechanicsEngineeringPhysicsElectrical engineeringComputer science

Abstract

fetched live from OpenAlex

With the increasing demand for efficient, power-dense, and reliable power systems in aerospace applications, the thermal management of high-power electronic components has become a critical challenge. High-power common-mode chokes, essential components for electromagnetic interference (EMI) suppression, generate significant heat during operation, necessitating effective cooling techniques to maintain optimal performance and prolong their lifespan. This paper presents the design of a novel cylindrical jet impingement cooling system specifically tailored for high-power common-mode chokes in aerospace applications. The proposed cooling system leverages the advantages of jet impingement cooling to achieve enhanced heat transfer and temperature uniformity across the magnetic core as well as the bus bar while offering a competitive mass reduction compared to similar devices. A cylindrical configuration is chosen to accommodate the geometric constraints of the magnetic core and bus bar configuration used in such applications. Mathematical modelling in partnership with computational fluid dynamics (CFD) simulations is employed to evaluate the thermal as well as pressure drop performance of the system.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.529

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)0.0000.000

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 head0.017
GPT teacher head0.257
Teacher spread0.240 · 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
GenreMethods

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
Published2024
Admission routes2
Has abstractyes

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