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Record W4410314906 · doi:10.1115/1.4068668

Design, Fabrication, and Testing of a Polymer Expanded Heat Exchanger for Absorption Chilling

2025· article· en· W4410314906 on OpenAlexaff
Zion Alioto, Joshua M. Pearce, Baxter Kamana-Williams, David Denkenberger

Bibliographic record

VenueJournal of Thermal Science and Engineering Applications · 2025
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceHeat exchangerFabricationPolymerAbsorption (acoustics)Copper in heat exchangersPlate fin heat exchangerNuclear engineeringComposite materialPlate heat exchangerMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract The increasing demand for energy-efficient and environmentally friendly cooling technologies has driven the exploration of advanced heat exchanger (HX) designs. Traditional metal HXs, while effective, are often heavy, expensive, and prone to corrosion. This study addresses these challenges, presenting the design, fabrication, and testing of a polymer expanded heat exchanger (PEHX) for a high-pressure, water–ammonia–helium absorption refrigerator. Utilizing open-source laser welding and 3D printing, the PEHX was constructed from linear low-density polyethylene and acrylonitrile butadiene styrene. The PEHX achieved an effectiveness of 0.62, a 13% improvement over the existing heat exchanger's 0.55, potentially reducing the refrigerator's power consumption by 5 W. Over a 10-year lifespan, this could save approximately 453 kWh of energy, equivalent to electricity costs of $68 and greenhouse gas emissions of 321 kg(CO2,e). However, the PEHX exhibited a higher pressure drop than the existing heat exchanger, necessitating further design improvements, including optimized welding techniques, alternative flow patterns, and redesigned headers to reduce pressure drop. This work demonstrates the potential of additive manufacturing of polymer heat exchangers for applications requiring lightweight, cost-effective, and corrosion-resistant heat transfer solutions, and highlights areas for future research.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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