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Record W2023356070 · doi:10.5539/mas.v3n7p32

Simulation of Gravity Feed Fuel for Aeroplane

2009· article· en· W2023356070 on OpenAlexvenueno aff
Yaguo Lu, Zhenxia Liu, Shengqin Huang, Tao Xu

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAircraft fuel systemProcess (computing)Transient (computer programming)Fuel tankSafety valveFuel efficiencyFuel mass fractionComputer scienceAutomotive engineeringEnvironmental scienceSimulationEngineeringVapor lockMechanical engineering

Abstract

fetched live from OpenAlex

Gravity feed is one fuel supply way for aeroplane and the simulation of it is very important. The traditional method to calculate the gravity feed is to assume that only one tank in fuel system supplies the needed fuel to the engine, and then calculated for the single branch. Actually, all fuel tanks compete for supplying fuel and the key problem for gravity feed calculation is to simulate the multiple-branch and transient process. The present paper gives the mathematical model for fuel flow pipe, pump, check valve and the simulation model for fuel tank at first, and then presented a new calculation model for gravity feed fuel of aeroplane fuel system based on the flow network theory and time difference method. The model takes into consideration all fuel tanks and can solve the multiple-branch and transient process of gravity feed. Finally, the thesis gives a numerical example for a certain type of aircraft, achieved the variations of fuel level and flow mass per second of each fuel tanks, the variations of the fuel pressure at the engine inlet, and predicted the maximum time that the aeroplane could fly safely under gravity feed. The numerical example indicts that the method proposed here is intrinsically superior to the traditional methods and is closer to understanding the real seriousness of the fuel supply situation.

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: none
Teacher disagreement score0.928
Threshold uncertainty score0.336

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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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
Published2009
Admission routes1
Has abstractyes

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