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Record W2317617653 · doi:10.1080/14786451.2012.744020

Energetic and exergetic analyses of a hydrogen-fuelled HCCI engine for environmentally benign operation

2012· article· en· W2317617653 on OpenAlexaff
Abdul Khaliq, Farrukh Khalid, Priybrat Sharma, İbrahim Dinçer

Bibliographic record

VenueInternational Journal of Sustainable Energy · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsExergyExergy efficiencyEnvironmental scienceEfficient energy useHydrogenWork (physics)Nuclear engineeringWork outputThermodynamicsHomogeneous charge compression ignitionRange (aeronautics)Ignition systemProcess engineeringMaterials scienceWaste managementChemistryCombustionEngineeringCombustion chamberPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, combined first and second law approach is applied to investigate the effects of percent excess air and ambient temperature on the energy and exergy efficiency of the hydrogen-fuelled homogeneous charge compression ignition engine. A maximum energy efficiency of 45% and an exergy efficiency of 37% are obtained at the excess air of 25%. A narrow range of 42–40% energy efficiency and a wide range of 25–45% exergy efficiency were achieved between the 20–40% excess air and an ambient temperature of 300 K. Close range of variation for energy efficiency (48–44%) and exergy efficiency (32–36%) were achieved between the ambient temperatures of 13°C and 41°C. Exergy analysis indicates that 52% of the fuel hydrogen exergy is destroyed due to various irreversible processes of the engine, around 40% is available as a useful work output, and 7.83% is lost via engine exhaust.

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: none
Teacher disagreement score0.664
Threshold uncertainty score0.519

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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

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