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Record W4408151016 · doi:10.11159/jffhmt.2025.008

Improving Oil Cooling Efficiency Using Polymeric Hollow Fibers

2025· article· en· W4408151016 on OpenAlexvenueno aff
Filip Lang, Erik Bartuli, Jiří Hvožďa, Tereza Kroulíková, Martin Beran, Jiří Kučera

Bibliographic record

VenueJournal of Fluid Flow Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
FundersVysoké Učení Technické v Brně
KeywordsMaterials scienceProcess engineeringComposite materialPetroleum engineeringEngineering

Abstract

fetched live from OpenAlex

Oil cooling plays a critical role across various industries, such as transformer cooling, automotive, computing, and aerospace.This study introduces an innovative approach to oil cooling, utilizing a thin-walled polymeric hollow fiber heat exchanger.Research mainly focuses on oil cooling in combustion engines, which represent one of the most widespread applications.The designed cooling system is highly adaptable for a wide range of applications.The presented solution offers an attractive alternative characterized by low energy consumption, reduced CO2 emissions, and high specific heat transfer performance.The innovative approach lies in the use of polymer hollow fibres instead of standard aluminium heat exchangers.This strategy also saves space in the engine compartment as the heat exchanger is located in the engine oil sump.This heat exchanger is manufactured from polyamide (PA612) with an outer fiber diameter of 1 mm.Despite the low thermal conductivity of PA612, the polymeric hollow fibre heat exchanger has low thermal resistance owing to its thin wall thickness of only 0.08 mm.The proposed solution underwent rigorous testing on a combustion engine test rig capable of simulating real-world engine operating conditions.The results show that the designed cooling system achieved thermal outputs up to almost 1250 W (with a water flow rate of 1.5 lmin-1 in the heat exchanger).The engine coolant temperatures did not exceed 83.5 C, remaining within the standard limits.Thus, the proposed system fulfils its function as an oil cooling 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.609
Threshold uncertainty score0.642

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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
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
Published2025
Admission routes1
Has abstractyes

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