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Record W4415927350 · doi:10.15353/hi-am.v1i1.6777

Thermo-hydraulic performance of uniform and hybrid Triply Periodic Minimal Surfaces (TPMS) heat exchangers

2025· article· W4415927350 on OpenAlexaff
Armin Hassanirad, Collins Chike Kwasi-Effah, Osezua Ibhadode

Bibliographic record

VenueProceedings of the Holistic Innovation in Additive Manufacturing (HI-AM) Conference · 2025
Typearticle
Language
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHeat exchangerHeat transferDiamondComputational fluid dynamicsYield (engineering)Base (topology)TurbulenceHeat spreader

Abstract

fetched live from OpenAlex

Triply Periodic Minimal Surfaces (TPMS) geometries are remarkable solutions for achieving optimal heat transfer performance in industries where space-efficient cooling solutions are required. Utilizing these additively manufactured geometries in Heat Exchanger (HX) applications involves a trade-off between maximizing heat transfer and minimizing pressure drop. While prior studies mostly focused on uniform TPMS-based HXs, this research investigates the thermo-hydraulic performance of both uniform (Gyroid, Diamond D, and FRD) and hybrid (Gyroid-FRD, Diamond D-Gyroid, and Diamond D-FRD) TPMS-based HXs. In this study, TPMS geometries were generated via LattGen, and design setup and Computational Fluid Dynamics (CFD) simulation were conducted using Ansys Fluent 2023 R2. All geometries were generated at 30% relative density, and hybrid transitions were achieved via the Sigmoid function. A k-epsilon turbulence model was employed for CFD analysis, and the model was validated against existing literature. Results illustrate that the FRD HX exhibits the best temperature change performance, corresponding to a 13.9 [K] increase in temperature, while introducing a 239.58 [Pa] pressure drop. Among hybrids, Diamond D-FRD HX enabled 13.82 [K] temperature change, improving base uniform FRD flow resistance by 62.5%. The investigation reveals that hybridization can yield an intermediate of thermo-hydraulic performance characteristics from their uniform base structures.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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.

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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