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Record W78581360

Canadian Forces Experience with Turbofan HCF - Case Study

2005· article· en· W78581360 on OpenAlexaboutno aff
Corey Kinart, P Thériault

Bibliographic record

VenueDefense Technical Information Center (DTIC) · 2005
Typearticle
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsnot available
Fundersnot available
KeywordsTurbofanEngineeringTube (container)Automotive engineeringDamperGimbalVibrationStructural engineeringMechanical engineeringAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

High Cycle Fatigue (HCF) cracking of a Canadian Forces (CF) turbofan engine fuel tube resulted in a six year, multinational effort to identify the root cause and to ultimately develop and implement a solution. The second of three fuel tube failures experienced by the CF during this timeframe resulted in an engine fire that caused significant damage to a military aircraft, underlining the seriousness of the issue at hand. With HCF identified as the mechanism of failure, efforts focused on vibration input to the fuel tube during engine operation. An experiment was developed to instrument an in-service fuel tube and perform comprehensive flight tests to quantify the strains experienced by the tube and identify vibration frequencies that required mitigation in order to eliminate HCF failures. A damper bracket was developed to shift the modal response of the fuel tube away from damaging frequencies experienced in-flight. The prototype bracket then required the addition of an adjustable feature that would allow it to accommodate slight variability in the location of mounting points from engine to engine. In addition, modification of some existing hardware was also required in order to implement the final solution. Production damper brackets were installed on all in-service engines, and to date have prevented any further fuel tube failures.

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: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.957

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 communication0.0000.001
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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