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Record W2018190854 · doi:10.1109/ecce.2013.6646981

A comparison of thermal vias patterns used for thermal management in power converter

2013· article· en· W2018190854 on OpenAlexaff
Deepak Gautam, Fariborz Musavi, Dale Wager, Murray Edington

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsDelta-Q Technologies (Canada)
Fundersnot available
KeywordsThermalPower electronicsElectronicsPower (physics)Thermal management of electronic devices and systemsComputer scienceThermal analysisPower modulePower semiconductor deviceHeat sinkMaterials scienceElectronic engineeringMechanical engineeringElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A daunting challenge in packaging design for power electronics products is removing the heat from the power devices in a cost effective manner. In this paper, a thorough literature review of the design and analysis of thermal vias in PCBs for thermal management of power electronics devices are presented. Based on the results from the available literature and practical manufacturing guidelines, four different via patterns for single power devices are selected. Each of the four via patterns is laid out multiple times with their via holes are filled with a filler material and their performance are compared to non-filled thermal vias. One dimensional analysis is performed to characterize the thermal performance of the thermal via patterns. The experimental results presented closely matches the theoretical prediction to identify the most efficient thermal via pattern.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.253
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2013
Admission routes1
Has abstractyes

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