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Record W4409345074 · doi:10.19206/ce-203003

Micro gas turbine evolution, a quarter-century review

2025· review· en· W4409345074 on OpenAlexaboutno aff
Michał Czarnecki

Bibliographic record

VenueSilniki Spalinowe/Combustion Engines · 2025
Typereview
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Gas turbinesHistoryMechanical engineeringEngineeringArchaeology

Abstract

fetched live from OpenAlex

The presented article outlines the changes that have occurred over the past quarter-century in the design and performance of micro class gas turbine engines. The primary goal is to determine the current stage of development in engine construction. To achieve this, a representative group of 83 micro-class engines was selected and categorized based on the date they were introduced into operation. The main performance criterion was the engine's thrust, as these types of engines are primarily used in short-lifespan unmanned aerial vehicles (UAVs). A rotational performance characteristic was identified for a family of engines grouped into three geometric series. These characteristics are presented in relative parameters, facilitating convenient implementation in UAV design. A new trend in fanjet engine construction was identified, where thrust generation is primarily driven by the mass flow of the working medium passing through the engine duct. This is observed in modern engines with thrust exceeding 20 daN. It was demonstrated that, while maintaining the same external dimensions, a contemporary engine can deliver three times the thrust of a similar engine designed at the beginning of the 21st century.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.010
GPT teacher head0.252
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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