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Record W4417486588 · doi:10.1016/j.ngib.2025.11.007

Research progress on numerical simulation methods and models for underground coal gasification

2025· article· en· W4417486588 on OpenAlexaff
Xiang’an Lu, Shanshan Chen, Zhen Dong, Jin Sun, Liangliang Jiang

Bibliographic record

VenueNatural Gas Industry B · 2025
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsUniversity of Calgary
FundersYangzhou UniversityPetroChina Company Limited
KeywordsUnderground coal gasificationCoal gasificationCoalComputer simulationWood gas generatorHeat transferSpallProcess (computing)

Abstract

fetched live from OpenAlex

Coal underground gasification (UCG) transforms the physical extraction of coal into the chemical extraction of gas, which is effective for exploiting deep coal deposits. Numerical simulation technology for UCG is a crucial tool for studying the complex processes involved in coal gasification. This study was conducted to determine the direction in which UCG numerical simulation is developing, specifically by reviewing the research progress and achievements made in this area and identifying the existing problems and future research directions. The findings indicate the following: (1) Research has focused on the reaction issues of coal underground gasification, considering mass and heat transfer effects and gasification cavity expansion. Chemical equilibrium, gasification block, packed bed, and gasification channel models have been developed, which have certain advantages in solving gasification reaction problems influenced by cavity structure and reasonable simplifications capable of describing local issues. (2) The dynamic description of gasification cavity structures is a challenging problem that UCG numerical simulation needs to address. The cavity expansion mechanism includes thermochemical consumption, coal spalling, roof collapse, and debris accumulation. Thermochemical consumption causes the mechanical properties of coal and rock to change, leading to spalling under stress. (3) Process models emphasize dynamic simulations of the gasification process, including cavity evolution and gasification products. The reactor combination model, continuous medium equivalent model, and multimodule integration model are primarily used. (4) Future UCG numerical simulation technology development will prioritize modularity, systematization, and intelligence. There is an urgent need to facilitate the chemical reaction kinetics of large coal blocks, the coupling of discontinuous media, and the integration of multifunctional systems, including that of numerical simulation technology with artificial intelligence. With continuous improvements, numerical simulation technology will play a greater technical supporting role in UCG industrialization.

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)0.002
metaresearch head score (Gemma)0.005
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: Review · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.121
GPT teacher head0.460
Teacher spread0.339 · 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
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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