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Record W4318537928 · doi:10.5944/bicim2022.266

Generación de hidrógeno a partir de la gasificación solar de combustibles sólidos utilizando un reactor de medios porosos híbrido

2022· article· es· W4318537928 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

VenueCongreso Iberoamericano de Ingeniería Mecánica-CIBIM 2022 · 2022
Typearticle
Languagees
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Hidrógeno (H2) y gas de síntesis pueden ser producidos a partir de diversas fuentes mediante reformado de vapor y oxidación parcial. La combustión híbrida filtrada (HFC) consiste en la gasificación de combustibles sólidos o, simultáneamente, en el reformado de combustibles gaseosos y sólidos, sosteniendo reacciones homogéneas y heterogéneas, alcanzando altas temperaturas en el frente de reacción. Este trabajo desarrolla un modelo matemático para generar H2 utilizando un reactor HFC, mediante gasificación del combustible sólido con aporte solar, utilizando COMSOL Multiphysics. Se consideró un lecho poroso de esferas de alúmina y partículas de carbón sub-bituminoso dispuestas aleatoriamente y concentrando la energía solar mediante una placa emisora. El rendimiento de hidrógeno fue 86.5%, eficiencia solar-combustible 49.5% y eficiencia energética 72.3% para 600 kW/m2 de potencia solar. En base a los resultados, esta investigación proyecta la producción de H2 a partir de combustibles fósiles, representando una línea base para la gasificación solar.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0040.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.016
GPT teacher head0.295
Teacher spread0.278 · 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