MétaCan
Menu
Back to cohort
Record W7119522874 · doi:10.1115/icef2025-164179

A Flexible High Pressure Gaseous Fuel Injector for IC Engine Research

2025· article· W7119522874 on OpenAlexaffabout
Jeffrey Galbraith, James S. Wallace

Bibliographic record

Venuenot available
Typearticle
Language
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInjectorFuel injectionCompressed natural gasNozzleNatural gasHigh pressure

Abstract

fetched live from OpenAlex

Abstract High pressure gaseous injectors for engine research are difficult to source. Gaseous injectors that are available are patterned after GDI injectors and typically limited to injection pressures around 1 MPa, which can only be used for injection early in the compression stroke. Gaseous injectors for higher injection pressures are typically prototypes with very limited availability and high cost. Around 1990, the Engine Research and Development Lab at the University of Toronto developed a high pressure gas injector with adjustable operating parameters to provide flexibility for various research needs. The injector features e-coil solenoid actuation, an inwardly opening pintle, and a removable injector tip that facilitates ready substitution of different injector nozzle geometries. This paper describes the many design refinements and operational insights made over several decades of extensive in-use experience for natural gas IC engine research. In its current state, the injector can operate at a maximum input pressure of 12.4 MPa absolute, an operating frequency up to 1600 cycles per minute, and with a minimum 0.75 ms injection duration. Using natural gas the injector has negligible leakage when closed. Recommendations for further development are made. The design could be adapted by other engine researchers for gaseous fuel research projects.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.365
Teacher spread0.325 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2025
Admission routes2
Has abstractyes

Explore more

Same topicAdvanced Combustion Engine TechnologiesFrench-language works237,207