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Record W2092603825 · doi:10.1109/dasc.2004.1390738

Development of a fault tolerant flight control system

2005· article· en· W2092603825 on OpenAlexaff
C.B. Feldstein, J.C. Muzio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAvionicsFault toleranceResilience (materials science)Modular designEmbedded systemFault (geology)Control systemComputer scienceScope (computer science)Software fault toleranceLife-critical systemIntegrated modular avionicsFault modelReliability engineeringEngineeringDistributed computingSoftwareOperating systemAerospace engineering

Abstract

fetched live from OpenAlex

This work discusses the design and development of a fault tolerant flight control system as a part of the research requirement of the Author's Master's Degree Thesis. The requirements of safety critical systems, reliable systems, fault tolerant systems, avionics and embedded systems were considered for this project. Byzantine resilience and common mode fault avoidance are considered beyond the scope of this work at this time. The fault tolerant system designed for this work was set up as a triple modular redundant system to tolerate the existence of one fault within the system. The system was implemented with the PC/104 embedded PC platform. Microsoft flight simulator was used as a test platform to generate input data and to demonstrate successful operation by showing a flight under control by the flight control system. The end results show that a fault tolerant system can be developed to successfully tolerate one fault while the system is in operation.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.214
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 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

Citations17
Published2005
Admission routes1
Has abstractyes

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