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Record W3154672739 · doi:10.22215/etd/2020-14176

Transient Mathematical Modelling of Loop Heat Pipes and Experimental Validation

2020· dissertation· en· W3154672739 on OpenAlexaff
Hooman Jazebizadeh

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsLoop heat pipeHeat sinkHeat transferTransient (computer programming)MechanicsMechanical engineeringMaterials scienceEngineeringHeat pipeComputer science

Abstract

fetched live from OpenAlex

Development of state of the art electronics forces thermal engineers to develop more efficient and innovative heat transfer devices. Modern electronics do not only dissipate more heat per area but also their operation is subject to temperature stability. Loop Heat Pipes offer an important advantage over other heat transfer devices with their unique characteristics. These self-regulated devices utilize the latent heat of the working fluid circulating between a hot source and cold sink by using thermodynamic principles and capillary forces. Experimental work is performed, on two different LHPs under ambient conditions, to investigate the operational characteristics of LHPs and to collect data under different operating conditions for the validation of the numerical model developed in this research. The main investigated characteristics comprise of the operating temperature and its oscillations at given operating conditions, the LHP response to a change in the operating conditions, and the location of the two-phase/liquid interface inside the LHP condenser. Furthermore, the empirical correlations, required to calculate the LHP heat transfer coefficients and pressure drops, are chosen and verified for the numerical model. Following the correlation verification, a modular numerical model is developed and validated to predict the steady-state and transient operation of an LHP with minimum accommodation parameters. The sensitivity studies of the modelling parameters are conducted to investigate their effects on LHP operation. The model can be easily modified or improved because of its modularity feature. Additionally, the minimum number of the accommodation parameters allows the model to predict LHP behavior by relying on only one set of power cycling test results. The mathematical model can be used not only as a design tool in the research and development of new LHPs but also to examine and troubleshoot the operation of an existing LHP in remote locations such as onboard a satellite orbiting Earth.

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 score0.335
Threshold uncertainty score0.605

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 head0.030
GPT teacher head0.252
Teacher spread0.222 · 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
Published2020
Admission routes1
Has abstractyes

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