MétaCan
Menu
Back to cohort
Record W2789982607

Year-round biodiesel use strategy in diesel engines in Canadian adverse cold weather conditions

2017· dissertation· en· W2789982607 on OpenAlexaboutno aff
Arvind Mangad

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBiodieselDiesel fuelEnvironmental scienceAdverse weatherAeronauticsMeteorologyEngineeringAutomotive engineeringGeographyBiology
DOInot available

Abstract

fetched live from OpenAlex

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.250
Teacher spread0.218 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueKnowledge Commons (Lakehead University)Same topicBiodiesel Production and ApplicationsFrench-language works237,207