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Record W2007290845 · doi:10.1115/ipack2005-73039

Performance Characterization of a Thermal Management Concept for High-Density, High-Speed Parallel Optical Interconnects

2005· article· en· W2007290845 on OpenAlexaff
Alex Vukovic, Michel Savoie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsRackThermalThermal management of electronic devices and systemsComputer sciencePower (physics)Heat pipeChannel (broadcasting)TransmitterOptical powerMaterials scienceMechanical engineeringTelecommunicationsEngineeringOpticsHeat transferPhysics

Abstract

fetched live from OpenAlex

Parallel optical interconnects (POIs) offer capacity advantages for high-density telecomm requirements. Once an array of multi-channel, high-capacity POIs is placed on a board, shelf or telecom rack, it creates a challenging thermal management task. To develop a thermal management concept for high dissipating racks (over 10 kW), capable of keeping a maximum temperature of 80°C for optical components, with tight temperature uniformity requirements of ±1°C between a receiver (Rx) and transmitter (Tx), a fully functional two-shelf telecommunication rack has been built. A thermal management solution was proposed and was based on the implementation of heat pipes embedded into each board. The performance of embedded heat pipes is characterized for densely packaged, high-speed optics applications requiring temperature uniformity and stringent temperature limits. The proposed solution completely meets requirements of power-dense, high speed POIs at the board/shelf level for the typical telecommunication rack. Moreover, it evolves into an enabling strategy for the reliable control of power-dense, temperature-sensitive optical components.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.433

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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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