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Record W3000356871 · doi:10.3390/pr8010090

Model-Based Safety Analysis for the Fly-by-Wire System by Using Monte Carlo Simulation

2020· article· en· W3000356871 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcesses · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsUniversity of Manitoba
FundersFundamental Research Funds for the Central UniversitiesAeronautical Science Foundation of ChinaNanjing University of Aeronautics and AstronauticsNational Natural Science Foundation of China
KeywordsAirworthinessMonte Carlo methodReliability engineeringSystem safetyComputer scienceSimulationEngineeringAutomotive engineeringMathematics

Abstract

fetched live from OpenAlex

Safety analysis is one of the important means to show compliance with airworthiness requirements. The traditional safety analysis methods are significantly dependent on analysts’ skills and experiences. A model-based safety analysis approach is proposed for typical fly-by-wire (FBW) systems based on the system development model built via Simulink, by which the response of system performances can be simulated. The safety requirements of the FBW system are defined by presenting the thresholds of system performance metrics, and the effects of failure conditions on aircraft safety are determined according to the system response simulation by injecting failures or failure combinations into the Simulink model. The Monte Carlo simulation method is used to calculate the probability of unsafe conditions, whose effects are determined by the system response simulation with fault injections. Finally, a case study is used to illustrate the effectiveness and advantages of our proposed approach.

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.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.982
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.146
GPT teacher head0.374
Teacher spread0.229 · 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