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Record W4307887052 · doi:10.1139/tcsme-2022-0061

Effects of injection parameters on CRDI-equipped stationary diesel engine fuelled with neat biodiesel mix derived from waste feedstocks

2022· article· en· W4307887052 on OpenAlexvenueno aff
M. Anto Alosius, Pushparaj Thomai, Vikas Sharma

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDiesel engineNOxCombustionDiesel fuelBiodieselThermal efficiencyAutomotive engineeringEnvironmental scienceMean effective pressureDwell timeWaste managementSmokeInternal combustion engineIgnition systemCompression ratioChemistryEngineering

Abstract

fetched live from OpenAlex

This present work deals with the effects of injection parameters such as pilot-main injection mass ratio and dwell time on combustion, performance, and emission characteristics of a diesel engine. A single cylinder diesel engine is used in this research work with the flexibilities to modify different variables via open electronic control unit. Biodiesel mix (BDM) used in the present work is derived from waste feedstocks of used cooking oil and chicken fat. Throughout the experiment, engine load and speed were maintained constantly at 4.51 brake mean effective pressure and 1500 rpm, respectively. Different pilot mass ratios (10%, 20%, and 30%) and dwell times (20° crank angle (CA), 30° CA, and 40° CA) were tested and results were compared with conventional mode combustion. The results indicated that the pilot injections helped to reduce the ignition lag period and also shortened the combustion duration. The highest brake thermal efficiency of 34.78% was identified with the lowest pilot mass of 10%. According to the results, increased dwell time decreased the oxides of nitrogen emissions but increased the hydrocarbon emissions. The experiment revealed that BDM made of waste feedstocks could be an effective alternative for engine applications with optimized engine operating conditions.

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 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: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.176
Teacher spread0.168 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicBiodiesel Production and ApplicationsFrench-language works237,207