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Record W3129979464

Development of Technologies for RNG Utilization

2018· article· en· W3129979464 on OpenAlexfundno aff
Partho Sarothi Roy

Bibliographic record

VenueeScholarship (California Digital Library) · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
FundersUniversity of California, RiversideYeungnam UniversityClimate Change and Emissions Management CorporationLouisiana State UniversityCalifornia Energy Commission
KeywordsSyngasSteam reformingMethaneMethane reformerRenewable energyTonneCokeWaste managementMethanolIntegrated gasification combined cycleSyngas to gasoline plusCatalysisEnvironmental scienceProcess engineeringChemical engineeringChemistryHydrogen productionEngineeringOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Renewable energy production processes have achieved significant technological and commercial maturity over the past two decades. Most carbon based renewable fuel gases contain significant quantities of CO2. Converting the CO2 along with methane into syngas is an attractive option since it can potentially increase utilization of distributed renewable carbon resources while creating additional revenue streams.An integrated renewable power generation system where the SBR process was coupled with a Solid Oxide Fuel Cell (SOFC) was studied using the Aspen Plus model. The steam-biogas reforming (SBR) process performed over a Pd-Rh catalyst was compared with equilibrium values predicted by Aspen Plus. At steam to carbon ratio of 1.50 and temperature of 1073 K or above, positive CO2 conversion was obtained. Coke formation was significantly reduced during reforming reaction performed experimentally over the Pd-Rh compared to literature data. SBR integrated with combustion process works with an efficiency of 40% or higher. The variation of the catalytic support material composition helps to adjust H2/CO ratio and H2/CH4 yield. CeZrO2 addition suppressed coke formation, for improved oxygen storage and oxide reducibility. Pd-Rh catalysts exhibit stable performance for 200 h, although sintering occurred regardless the catalyst composition used.A life cycle assessment was performed for methanol production pathway using syngas produced via bi-reforming pathway from CO2, H2O reforming with methane. GHG emission is about 203 kilograms of CO2e per metric tonne of methanol produced using the proposed bi-reforming pathway. GHG emission reduction is 0.29 kg/ CO2e/kg of CH3OH compared to the commercial scale production. With NG price $3.50/GJ and methanol price $400/tonne IRR is 57% with 5 years payback period.A database for Wobbe Index, Methane Number, thermal conductivity, sound velocity of biogas, anaerobic digester gas and natural gas mixture was built. A prediction model for WI and MN of a gaseous fuel mixture was developed that uses thermal conductivity and sonic velocity. The model can predict the Wobbe Index with an average error of ±2.76% and Methane Number with an average error of ±1.65%. The prediction model coupled with a thermal conductivity sensor and sonic velocity measurement sensor enables the combustion of gas efficiently.

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)0.001
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: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.246
Teacher spread0.217 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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