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Record W2056084164 · doi:10.1115/ices2003-0548

Hydrogen Fuelled Spark-Ignition Engines: Predictive and Experimental Performance

2003· article· en· W2056084164 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDesign, Application, Performance and Emissions of Modern Internal Combustion Engine Systems and Components · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSPARK (programming language)CombustionIgnition systemHydrogen vehicleSpark-ignition engineAutomotive engineeringHydrogenComputer scienceIgnition timingHydrogen fuelHomogeneous charge compression ignitionHydrogen technologiesInternal combustion engineEnvironmental scienceProcess engineeringNuclear engineeringCombustion chamberAerospace engineeringEngineeringChemistryHydrogen economy

Abstract

fetched live from OpenAlex

Hydrogen is well recognized as a suitable fuel for spark-ignition engine applications that has many unique attractive features and limitations. It is a fuel that can continue potentially to meet the ever increasingly stringent regulations for exhaust and greenhouse gas emissions. The application of hydrogen as an engine fuel has been tried over many decades by numerous investigators with varying degrees of success. The performance data reported often tend not to display consistent agreement between the various investigators mainly because of the wide differences in engine type, size, operating conditions used and the differing criteria employed to judge whether knock is taking place or not. With the ever-increasing interest in hydrogen as an engine fuel, there is a need to be able to model extensively various features of the performance of spark ignition (S.I.) hydrogen engines so as to investigate and compare reliably the performance of widely different engines under a wide variety of operating conditions. The paper employs a quasi-dimensional two-zone model for the operation of S.I. engines when fuelled with hydrogen. In this approach, the engine combustion chamber at any instant of time during combustion is considered to be divided into two temporally varying zones: a burned zone and an unburned zone. The model incorporates a detailed chemical kinetic model scheme of 30 reaction steps and 12 species, to simulate the oxidation reactions of hydrogen in air. A knock prediction model, developed previously for S.I. methane-hydrogen fuelled engine applications (Shrestha and Karim 1999(a) and 1999(b)) was extended to consider operation on hydrogen. The effects of changes in operating conditions, including a very wide range of variations in equivalence ratio on the onset of knock and its intensity, combustion duration, power, efficiency and operational limits were investigated. The results of this predictive approach were shown to validate well against corresponding experimental results of our own and those of others, obtained mostly in a variable compression ratio CFR engine. On this basis, the effects of changes in some of the key operational engine variables, such as compression ratio, intake temperature and spark timing are presented and discussed. Some guidelines for superior knock free-operation of engines on hydrogen are made also.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
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
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.230
Teacher spread0.211 · 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