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Record W4396621725 · doi:10.1016/j.csite.2024.104462

Condenser operating conditions effects on dielectric liquid boiling and condensation heat transfer in closed systems

2024· article· en· W4396621725 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCase Studies in Thermal Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCondenser (optics)BoilingCondensationMaterials scienceHeat transferThermodynamicsLiquid dielectricDielectricMechanicsOpticsPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

Localized boiling and enclosed condensation of a dielectric liquid in a thermosyphon can be used as an alternative to traditional air cooling for high performance microprocessors. A small quantity of dielectric fluid boils at the surface of the microprocessor and is condensed by a heat exchanger, which removes the heat from the system. Here, the heat exchanger was a water-fed cold plate cooling a round fins heat sink. Such a thermosyphon can remove large heat fluxes and increase the energy efficiency of data centers. An experimental setup was built to measure the impact of various operating parameters on the thermal resistances of the thermosyphon. The thermal resistances that were considered were the boiling resistance between the heater and the dielectric fluid, the condensation resistance between the dielectric fluid and the cold water feeding the cold plate, and their sum (the total thermal resistance). The operating parameters tested were the cold plate inlet flow rate (0.2 L/min and 1 L/min), the cold plate inlet temperature (15°C and 24°C) and the filling ratio of the enclosure (33%, 66% and 88%). It was observed that changing the filling ratio did not have a significant impact on the thermal resistances of the thermosyphon. Increasing the cold plate inlet flow rate from 0.2 L/min to 1 L/min and decreasing the cold plate inlet temperature from 24°C to 15°C both led to significantly lower total thermal resistance. However, increasing the flow rate lowered the rate at which the pressure increased with the amount of heat removed from the system, while this rate did not change when decreasing the cold plate inlet temperature. These observations could be properly explained by a simple analytical model, with a single free parameter (increasing the thermal resistance of the heat sink for the lowest cold plate flow rates). With the free parameter adjusted to the data, the model had a root-mean square error of 1.8°C and a maximum error of 6°C, over all measured conditions. This study demonstrates how changing the filling ratio or the cold plate inlet temperature and flow rate have an impact on the pressure, the temperature and the thermal resistances inside the thermosyphon. This is a first step in evaluating the energetic and economic efficiency of the thermosyphon solution for its future integration in data centers.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.124
Threshold uncertainty score1.000

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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