Year-round biodiesel use strategy in diesel engines in Canadian adverse cold weather conditions
Notice bibliographique
Résumé
The effects of climate change that have been seen at an unprecedented scale over last decade or so, have sparked intensive efforts toward the identification and development of clean, environmentally compatible, and renewable fuels. Biofuels such as alcohol and biodiesel have been identified as alternatives for powering internal combustion engines. When using vegetable oil as a feedstock for the production of biodiesel, major issues that arise include its poor low temperature properties. In this study, an experimental analysis was conducted to test the feasibility of biodiesel in cold climates specifically in Thunder Bay region and to suggest an appropriate solution for the biodiesel usage throughout the year. Weather reports from last decade were studied to compare with the cloud points of biodiesel blends. Biodiesel was produced from canola oil from transesterification and fractionation processes. Summer diesel and winter diesel have been used as reference fuels. Five different fuel series were used. The first series was summer diesel-biodiesel with ten blends (SB10, SB20, SB30, SB40, SB50, SB60, SB70, SB80, SB90 and B100). The second series was winter diesel-biodiesel with ten blends (WB10, WB20, WB30, WB40, WB50, WB60, WB70, WB80, WB90 and B100). The third series was winter diesel-biodiesel with 2 volume percent of (cold flow additive) Wintron Synergy series (WB20S2, WB50S2 and B100S2). The fourth series was winter diesel-fractionated biodiesel (FB20, FB50 and FB100). The final was winter diesel-fractionated biodiesel with 2 volume percent of Wintron Synergy series (FB20S2, FB50S2 and FB100S2). Except for winter diesel-biodiesel with 2 vol% synergy, all the fuel blend series were tested on two separate diesel engines; a four-cylinder heavy-duty diesel engine at constant speed of 800 rpm for emissions at idling condition followed by a two-cylinder light-duty diesel engine to investigate effects of fuel blends on performance and emission, under low, medium and high loads, at variable engine speeds of 1000 rpm, 2100 rpm and 3000 rpm. Results showed that normal biodiesel and fractionated biodiesel with 2 vol% synergy showed significant improvement in the cloud point. FB40S2 has the lowest cloud point compared to other fuel blends measuring -48.5?C. The effect of fuel blends on engine performance in light duty engine was investigated. The emissions of carbon monoxide (CO), hydrocarbon (HC), oxides of nitrogen (NOx) and smoke opacity from different fuel blends were measured and compared to summer and winter diesel fuels. In both the engines, fractionated biodiesel and synergy blends were found to be effective in reducing both CO and HC emissions. Smoke opacity emissions when compared from both the engines had a contrasting results. However, all biodiesel blends increased NOx emission. Results indicated that fractionated biodiesel with 2 vol% synergy had better engine performance, and lower emission compared with diesel fuel and normal biodiesel blends. Thus, fractionated biodiesel up to 80 vol% with 2 vol% synergy was found to be suitable for use in diesel engines in extreme winter conditions in Canada without the need for any engine modification.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».