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Record W4402851592 · doi:10.1016/j.energy.2024.133260

A multiphysics simulator for stope-coupled heat exchanger operation in deep underground mines

2024· article· en· W4402851592 on OpenAlexaff
Gongda Lu, Mohamed A. Meguid

Bibliographic record

VenueEnergy · 2024
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsMultiphysicsHeat exchangerEngineeringMining engineeringEnvironmental scienceNuclear engineeringPetroleum engineeringMechanical engineeringStructural engineeringFinite element method

Abstract

fetched live from OpenAlex

The ever-increasing mine depth offers unprecedented opportunities to access high-grade geothermal resources . By pre-installing pipeline systems in mined-out cavities before waste tailings placement, the stope-coupled heat exchanger (SCHE) has drawn growing attention for its superior socio-economic advantages. However, despite the extensive focus on energy efficiency, the system stability during heat production has been typically overlooked. This study therefore introduces a novel high-fidelity simulator for replicating practical SCHE operation. By embedding non-isothermal pipe flow into an evolutive thermo-poromechanics framework for cemented tailings, the outlet water temperature and multiphysics backfill response in diverse production settings are meticulously studied. Our calculations reveal for the first time that circulating chill fluid within mine backfill can substantially alleviate pressure development, suggesting enhanced system stability with heat-exchanger implementation. We also demonstrate that albeit targeting higher-grade geothermal resources, prioritizing cold-season operation, and pre-charging heat exchangers with production delays could spur heat productivity, the companion thermal pressure generation might still impose significant overloading risks. Conversely, while fast circulation would diminish the end-utilization temperature, the rapid heat removal could indeed facilitate superior efficiency and stability performance for the geothermal system . We believe these new findings hold critical implications for better positioning SCHE as a safely sustainable pathway towards hybrid utilization of deep resources.

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)0.000
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 score0.361
Threshold uncertainty score0.997

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 head0.018
GPT teacher head0.259
Teacher spread0.241 · 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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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