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Record W4403486965 · doi:10.1115/1.4066889

Design, Analysis, and Testing of an Additively Manufactured Catalytic Combustor for a Micro-Wave Rotor Turbine

2024· article· en· W4403486965 on OpenAlexaff
Αδάμος Αδάμου

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2024
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsSimon Fraser UniversityBP (Canada)
Fundersnot available
KeywordsCombustorRotor (electric)TurbineMechanical engineeringMaterials scienceEngineeringAutomotive engineeringAerospace engineeringChemistryCombustion

Abstract

fetched live from OpenAlex

Abstract In this paper, an additively manufactured (AM) Inconel catalytic combustor was tested in combination with a microwave rotor turbine with nonaxial channels designed for shaft power extraction. This was done in an open-loop configuration over a range of operating conditions in order to characterize the behavior of the wave rotor and combustor separately. The catalytic combustor data yielded low pressure losses of approximately 1% and provided stable and continuous operation up to outlet temperatures of 900 °C and combustion efficiencies of up to 99%. The data also revealed a high sensitivity to local over-fueling and hotspots that severely reduced service life. This is attributed to the additive manufacturing process producing uneven fuel injector hole sizes that cause uneven fuel mixing upstream of the catalytic reactor. However, it showed that first, it is possible to manufacture and coat an additively manufactured catalytic core. Second, it showed that the design freedom of AM could be used to make catalytic combustors viable in commercial applications.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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