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Record W4246272234 · doi:10.5383/ijtee.12.02.001

Performance Study of a Domestic Boiler Fueled By Biodiesel Produced From Rapeseed

2015· article· en· W4246272234 on OpenAlexvenueno aff
M. A. Hamdan, Derar Almomani

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBiodieselDiesel fuelWaste managementBoiler (water heating)Fuel oilEnvironmental scienceNOxFuel efficiencyBiofuelRapeseedBrake specific fuel consumptionWinter diesel fuelHeating oilPetroleumPulp and paper industryEngineeringChemistryCombustionAutomotive engineeringDiesel cycleCombustion chamber

Abstract

fetched live from OpenAlex

A domestic boiler was used in this work to compare its performance when it is powered by diesel fuel and biodiesel fuel that is produced from rapeseed oil, then blends of both fuels were prepared with different concentrations of biofuel (B5, B10 and B20). The performance measurements included the efficiency of the boiler, the specific fuel consumption in addition to the environmental impact represented by exhaust gases analysis; this included the concentration measurements of main species such as NOX, NO2, NO, SO2, CO2 and hydrocarbon. It was found that there is a small decrease in boiler efficiency resulting from using biodiesel fuel. Moreover, an increase in the specific fuel consumption has been noticed. The performance of a domestic boiler when operating using B20, B5 and B10 blends has similar fuel consumption and efficiency when it is powered by petroleum diesel fuel. The regulated emissions from biodiesel fuel found to be more ecological than petroleum diesel, with the concentrations of all pollutants decrease with the percentages of biodiesel in the blends.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.337

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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 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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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