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Record W4400058908 · doi:10.2118/220088-ms

Potential Evaluation of the Hydrogen Production in Underground Coal Gasification Process

2024· article· en· W4400058908 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoal gasificationUnderground coal gasificationProduction (economics)Process (computing)CoalHydrogen productionEnvironmental scienceWaste managementProcess engineeringHydrogenComputer scienceEngineeringChemistryEconomics

Abstract

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Abstract Under the new requirement of low-carbon energy transition, underground coal gasification (UCG) process has re-obtained much attention in recent years. It is a process of producing syngas by the underground in-situ conversion of solid coal resources. The main gaseous products include CO, CH4, and H2, and by-products such as CO2. Therefore, it also provides a new possibility and potential of hydrogen production from syngas. In this work, an experimental and numerical study is performed to evaluate the potential of hydrogen production in UCG process. First, a series of heat-treatment tests are conducted to gasify the coal samples. By using the methods of scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD), the microscopic pore structure and mineral transformation behavior of gasified coal samples can be evaluated. Simultaneously, from the SEM images, the element composition of gasified coal samplesis also discussed. Then, based on the laboratory observation, a field scale UCG simulation model is developed, which fully considered 10 complicated chemical reactions during UCG process, including pyrolysis, combustion and gasification processes. And it is also validated by comparing against the field test results of Swan Hills UCG test. In order to accurately evaluate the hydrogen production capacity, through adjusting the parameters of each chemical reaction, the fractions of gaseous products are also verified. Then, based on the simulation model, the factors that control the hydrogen production capacity are discussed, and the optimal operation procedure is also studied. Results show that with the temperature of heat treatment rises, the porosity and permeability of the gasified coal samples are obviously increased, and the mass loss rate has reached about 47%.The number and width of fractures in post heat-treated coal samples are also extremely increased. An exponential function relationship between porosity and permeability of gasified coal is obtained, and the obtained multiplier between porosity and permeability is about 14.93. The developed UCG simulation model can well simulate the coal gasification process. The fraction of hydrogen in syngas is about 20%, which indicates that the UCG process can be a potential source of hydrogen energy. Then, based on this model, the effect of some sensitive factors is discussed. A strategy of pure oxygen injection followed by oxygen/water co-injection is proposed to enhance the hydrogen production during UCG process. And through an optimization on the operation parameters, the maximum fraction of hydrogen in syngas can reach about 25%. The suggested injection time of oxygen/water co-injection is at the end of the first stage of combustion cavity expansion (30d), and the optimized mass ratio of oxygen/water is 1.5:1. As a typical clean coal technology, UCG process can be considered as an important source of hydrogen production in such a time of energy transition.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.302
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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