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Record W2053574290 · doi:10.1115/gt2014-26214

Development of New Engine Control for ETF40B Marine Turboshaft Engine

2014· article· en· W2053574290 on OpenAlexaboutno aff
A. B. Luebs

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringNavyAeronauticsAutomotive engineeringReliability (semiconductor)Power (physics)

Abstract

fetched live from OpenAlex

Vericor Power Systems (Vericor), the manufacturer of the ETF40B turboshaft engine used on the US Navy Landing Craft Air Cushion (LCAC) vehicles, has introduced a new Full Authority Digital Engine Control (FADEC) to replace the original FADEC currently in service in the Navy LCAC fleet. After several attempts to improve the reliability of the original FADEC to meet an acceptable standard, the original FADEC has remained unreliable in service. In 2008 Vericor initiated a self-funded development program to replace the original engine control. Alternative FADEC design approaches were considered and ultimately Safran Electronics Canada (SE-C) was selected to design and manufacture a single-channel purpose built embedded controller that would control ETF40B engine/LCAC application as well as other Vericor gas turbine engines. The design effort began in August 2010 and the first on-engine tests occurred in July 2011. Environmental/EMI qualification testing was accomplished to aggressive temperature, shock, vibration and Mil-Std-461F requirements leading to field deployment in the spring of 2013. This paper describes the requirements for this FADEC, its design pedigree, and the development and testing of the unit leading to US Navy use on the ETF40B equipped LCACs.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.545

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 head0.008
GPT teacher head0.205
Teacher spread0.198 · 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
GenreMethods

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
Published2014
Admission routes1
Has abstractyes

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