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Record W7015886475

Utilisation de matériau à changement de phase pour optimiser le stockage d'air comprimé et les performances des systèmes hybrides éolien-diesel

2018· other· fr· W7015886475 on OpenAlexaboutno aff

Bibliographic record

VenueSémaphore (Université du Québec à Rimouski) · 2018
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDiesel fuelPoison controlThermal stratification
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: Les génératrices utilisant le diesel alimentent les sites isolés en électricité au Canada. En vue de palier aux difficultés liées à l’utilisation de diesel, le système hybride éolien - diesel jumelé avec stockage par air comprimé offre une des meilleures options. Le système thermique par chaleur latente avec les capsules sphériques contenant le matériau à changement de phase (MCP) est adopté dans cette étude comme unité de stockage thermique à cause de sa grande densité thermique et une température stable pendant une bonne période lors du processus de chargement. Le matériau à changement de phase est sélectionné suivant une méthode scientifique, analyse hiérarchique de procédé (AHP). Cette unité de stockage thermique est intégrée dans le système hybride éolien - diesel pour permettre la suralimentation du moteur diesel dans le cas de système à moyenne échelle. Le système thermique est modélisé et simulé pour montrer la variation de la température pendant le chargement et déchargement de l’air. L’air stocké sous haute pression et une température déterminée sert à la suralimentation supplémentaire du moteur diesel. Ces deux variables thermodynamiques (pression et température) doivent être évaluées pour une amélioration de l’efficacité énergétique du moteur diesel.Enfin, les performances du moteur diesel sont déterminées en faisant une suralimentation supplémentaire sur un moteur dont les caractéristiques techniques sont connues. Pour le cas consideré, le MCP sélectionné selon AHP est Formic Acid. Et les résultats de simulation montrent une amélioration de performances du moteur diesel MAN D2876 E301 en termes de puissance, rendement et consommation spécifique. -- Mot(s) clé(s) en français : système thermique, suralimentation, matériau à changement de phase, diesel, éolien, AH, super Decisions. -- ABSTRACT: Diesel generators are used to supply electricity to isolated sites in Canada. To overcome the difficulties associated with the use of this fuel, the hybrid wind-diesel system coupled with compressed air storage offers one of the best options. A latent heat system with the spherical capsules containing the phase change material (PCM) is adopted as a thermal storage unit for this reaserch thanks to its high thermal density and a stable temperature outlet for a period during the charging process. The phase change material is selected according to a scientific method, Analytical hierarchy process. This thermal system is integrated in the hybrid wind-diesel system to allow the supercharging of the diesel engine for the medium-scale.The thermal system is modeled and simulated to show the variation of the temperature inside of the storage unit. Air stored at high pressure and a certain temperature is used for the supplementary supercharging of the diesel engine. These two thermodynamic variables (pressure and temperature) must be evaluated to improve the efficiency of the diesel engine. Finally, the performance of the diesel engine is determined by doing an extra supercharging on an engine whose technical characteristics are known. For the case considered, the PCM selected according to AHP is Formic Acid. And the simulation shows an improvement of the MAN D2876 E301 diesel engine in terms of power, efficiency and specific consumption. -- Mot(s) clé(s) en anglais : thermal system, supercharging, phase change material, diesel, wind, AHP, super Decisions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.232
Teacher spread0.211 · 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 designBench or experimental
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueSémaphore (Université du Québec à Rimouski)French-language works237,207