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Record W2977037801 · doi:10.19206/ce-2017-324

Modelling of the fuel injection of medium speed marine diesel engines

2017· article· en· W2977037801 on OpenAlexfundno aff
J. Monieta

Bibliographic record

VenueSilniki Spalinowe/Combustion Engines · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
FundersIndependent Electricity System Operator
KeywordsCrankshaftFuel injectionInjectorDiesel fuelAutomotive engineeringDiesel engineDiesel cycleCommon railCylinderCrankCombustionFlow (mathematics)Internal combustion engineTwo-stroke engineCombustion chamberEnvironmental scienceMechanical engineeringMechanicsPetrol engineEngineeringPhysicsChemistry

Abstract

fetched live from OpenAlex

The article presents the stages of fuel injection modeling of the four-stroke marine diesel engines as a set of functional blocks the of the fuel waves flow. The elaborated model includes the values of changing pressures in the combustion chamber and the course of changes of the pressure in spaces of the injection pump, injection pipe and the injector. Linear and local losses, as well as the conditions for the functioning were taken into account in stages of the fuel flow. The influence of different values of the engine load on the pressure course of the in individual spaces of injection apparatus and in the engine cylinder during the working cycle depending on the crank angle of rotation of the crankshaft have been simulated. The mathematical relationships were selected and the structural and experimental data are used, allowing the calculation of the parameters of interest for the simulated process.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.247
Teacher spread0.221 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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