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Record W2727801600

Jumelage éolien-diesel avec stockage d'air comprimé : modélisation de la suralimentation du moteur diesel

2014· article· fr· W2727801600 on OpenAlexaboutno aff
Philippe Beaulac

Bibliographic record

VenueSémaphore (Université du Québec à Rimouski) · 2014
Typearticle
Languagefr
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsPolitical scienceForestryArtGeography
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: Ce mémoire est le résultat d'une recherche qui visait le développement d'un modèle de moteur diesel à I'aide d'un logiciel commercial, GT Power. Ce modèle permet de tester certaines hypothèses pour optimiser la récupération d'énergie d'un système hybride éolien-diesel avec stockage d'air comprimé. L'énergie stockée sous forme d'air comprimé pourrait être utilisée afin de réduire la consommation en carburant du moteur diesel. Les résultats anticipés pourraient être utilisés dans des sites isolés du nord canadien, où l'énergie est beaucoup plus dispendieuse à rendre disponible aux consommateurs. La méthodologie préconisée consistait à relever des données de performances sur un groupe électrogène modifié avec des capteurs, charges résistantes, interface et apport d'air comprimé. Les données pouvaient être utilisées afin d'ajuster le modèle développé. Une fois le modèle bien ajusté, les hypothèses d'optimisation sont mises à I'essai avant de tenter de modifier le moteur physique en tant que tel. Les résultats obtenus ne sont pas aussi concluants que désirés, compte tenu du bris d'un capteur de pression critique et d'échéanciers trop serrés pour permettre de reprendre les essais. Par contre, les données colligées de la simulation du modèle démontrent que le modèle et donc le logiciel GT Power peuvent bel et bien fournir l'outil de confirmation souhaité pour justifier des travaux de modification de concept de moteur. -- Mot(s) clé(s) en français : GT Power, moteurs diesels, jumelage éolien-diesel, sites isolés. -- ABSTRACT: 
\nThis thesis is the result of researches which aimed to produce a diesel engine model using commercial software, GT Power. This model was intended to be used to verify certain hypothesis for optimizing the energy recuperation of a windmill-generator station with compressed air storage. The energy stored as compressed air could be used to reduce the fuel consumption of the generator's engine. The results could then be applied in isolated communities where the costs of supplying energy are very high. The preferred methodology for this study was to collect data from a test bench consisting of a generator modified with sensors, resistance charges, interface and compressed air inlet source. The data could then be used to adjust the model in order to reproduce the performance of the real engine. Once adjusted, the model could be used to design and adapt engine parameters for other regimes. The results obtained were not as concluding as desired, because during the manipulations, a critical pressure sensor was damaged and the tests could not be reconducted due to tight scheduling. On the other hand, the data collected was sufficient to confirm the validity of the model and the performance of the GT Power software to conduct this kind of experiment. -- Mot(s) clé(s) en anglais : GT Power, diesel engines, hybrid wind-diesel systems, isolated sites.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.187
Teacher spread0.181 · 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.

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
Published2014
Admission routes1
Has abstractyes

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