MétaCan
Menu
Back to cohort
Record W7033566264

Premixed ammonia-methane-air combustion

2001· dissertation· en· W7033566264 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2001
Typedissertation
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsCombustorCombustionAdiabatic processKinetic energyWork (physics)Adiabatic flame temperaturePremixed flameYield (engineering)
DOInot available

Abstract

fetched live from OpenAlex

To better understand the effects of ammonia as a fuel additive, both the adiabatic burning velocities and combustion emissions were determined for premixed methane-air and ammonia-methane-air flat flames. The experimental results of this work were compared to chemical kinetic (CHEMKIN III) and thermodynamic (STANJAN) simulations as well as literature values. The literature provided limited information on emissions from ammonia-methane-air flames. There was also a lack of information regarding the burning velocities of these mixtures. A flat flame burner was built on the basis of the design of the perforated plate burner of van Maaren et al. [1993]. This burner facilitated the direct measurement of the adiabatic burning velocity based on the measurement of the unburned gas velocity. Using a 5-gas analyzer and a chimney, NO, NO 2, CO, CO2 and O2 emissions from various mixtures of ammonia-methane-air were determined. The burning velocity data for methane-air mixtures was found to be in good agreement with the literature and chemical kinetic simulations. For additions of 1% to 4% ammonia in the fuel, both the experimental observations and kinetic simulations revealed premixed ammonia-methane-air flames yield lower burning velocities than pure methane-air flames and result in a significant increase in NO emissions. In agreement with Wendt et al. [1974], the formation of NO in these flames appeared to be independent of thermodynamic equilibrium.Dept. of Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .M356. Source: Masters Abstracts International, Volume: 40-03, page: 0741. Advisers: P. Henshaw; D. Ting. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueScholarship at UWindsor (University of Windsor)Same topicFish biology, ecology, and behaviorFrench-language works237,207