MétaCan
Menu
Back to cohort

Comprehensive Comparison of Chemical Kinetics Mechanisms for Syngas/Biogas Mixtures

2015· article· en· W2247020496 on OpenAlexafffund
Hsu Chew Lee, A. A. Mohamad, Lei‐Yong Jiang

Bibliographic record

VenueEnergy & Fuels · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsNational Research Council CanadaUniversity of Calgary
FundersNetworks of Centres of Excellence of CanadaBioFuelNet CanadaMcGill University
KeywordsSyngasShock tubeLaminar flame speedIgnition systemCombustionLaminar flowThermodynamicsChemistryCHEMKINMethaneAnalytical Chemistry (journal)Materials scienceHydrogenPremixed flameShock waveCombustorChromatographyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

The performance of the most commonly used chemical kinetics mechanisms is compared against a large set of experimental data, accumulated for syngas mixtures diluted with other gases such as CO 2, H 2 O, N 2, and CH 4 . These dilutes are pertinent to syngas/biogas mixtures and could have significant effects on the combustion characteristics. The laminar flame speed and ignition delay are used as quantitative metrics to compare the simulation predictions with the experimental data. The experimental data include ignition measurements obtained from shock tubes and rapid compressions, and flame speed measurements obtained from spherical bombs as well as counterflow configurations covering a wide range of temperature, pressure, and equivalence ratios. The mixture compositions are systematically categorized in this study. After exhaustive comparisons, it is found that the NUIG2013 mechanism is in closest agreement with the measured ignition delay and laminar flame speed for the investigated mixtures. However, the predictions deviated significantly from the measured ignition delays for the H 2 /CO/CO 2, H 2 /CO/CH 4, and H 2 /CO/CH 4 /CO 2 /H 2 O mixtures. We performed a sensitivity analysis on the ignition delay time of the H 2 /CO/CO 2, H 2 /CO/CH 4, and H 2 /CO/CH 4 /CO 2 /H 2 O mixtures, using the NUIG2013 mechanism to identify the reactions that are responsible for the deviations. We found that by adopting a much lower rate constant expression [ k 0 (CO 2 ) = 8.82 × 10 19 × T[K] −1.40 (cm 6 /mol 2 /s)] for H + O 2 (+CO 2 ) = HO 2 (+CO 2 ) (R2), the NUIG2013 mechanism could accurately predict the ignition delay time of the H 2 /CO/CO 2 mixture at low pressures ( P = 1.24–2.36 atm) and low temperatures (<1025 K) range. A new rate constant expression [ k 3 = 2.3 × 10 8 × T [ K ] 1.40 exp(−2850/T) (cm 3 /mol/s)] for the CH 4 + OH = CH 3 + H 2 O R3 reaction in the NUIG2013 mechanism is required to reconcile the discrepancy observed between the measured and simulated ignition delay time of the H 2 /CO/CH 4 and H 2 /CO/CH 4 /CO 2 /H 2 O mixtures at P = 32 atm. In addition, the newly fitted rate constant expression for R3 improved the performance of the NUIG2013 mechanism in predicting the ignition delay of H 2 /CH 4 at P = 5, 10, and 20 atm. More importantly, the modifications made to the reactions (R2) and R3 did not substantially affect the NUIG2013 mechanism’s excellent predictions of the flame speed. Hence, it is recommended that the rate constant expressions for (R2) and R3 be incorporated into the NUIG2013 mechanism for any study of the combustion characteristics of biogas/syngas mixtures.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.036
GPT teacher head0.281
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations27
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueEnergy & FuelsSame topicAdvanced Combustion Engine TechnologiesFrench-language works237,207