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Record W4401941245 · doi:10.1115/gt2024-126861

Effects of Lattice Orientation Angle on TPMS-Based Transpiration Cooling

2024· article· en· W4401941245 on OpenAlexaff
Juchan Son, Mohsen Broumand, Yeongmin Pyo, P. Richer, Bertrand Jodoin, Zekai Hong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
Fundersnot available
KeywordsOrientation (vector space)Lattice (music)TranspirationMaterials scienceComputer sciencePhysicsGeometryAcousticsChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract Establishing a continuous cooling film is an effective way to thermally protect hot-gas path components of gas turbines. For aero-engines, effusion cooling is the state-of-the-art method for developing cooling films. However, the cooling film generated by this method is far from ideal, as discrete miniature cooling air jets exiting from effusion cooling holes leave large gaps between cooling holes without adequate cooling film protection. Furthermore, effusion cooling jets can experience strong lift-off from component surfaces and are subsequently diluted due to mixing with the main flow. Recent advances in additive manufacturing (AM) technologies have enabled the fabrication of porous materials with precisely engineered lattice structures, significantly enhancing the film cooling effectiveness of hot-gas path components through transpiration cooling. A prior study has demonstrated highly promising transpiration cooling results by using a family of lattice geometries referred to as triply periodic minimal surface (TPMS) lattices. The present study experimentally investigates the influence of various TPMS lattice orientations on the film cooling effectiveness. Three types of TPMS structures, namely Diamond, Koch and Gyroid, are compared to demonstrate that the TPMS lattice orientation angle affects transpiration cooling performance, with different levels of sensitivity according to the TPMS structure. The TPMS lattice structures studied in this investigation are fabricated by stereolithography (SLA) 3D printing. The adiabatic cooling film effectiveness (AFE) is measured using pressure sensitive paint (PSP).

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.220

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 head0.223
Teacher spread0.216 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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