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Record W4408578495 · doi:10.1016/j.enbenv.2025.03.001

Numerical simulation of heat transfer through rock envelope of a plant factory in an underground mine tunnel

2025· article· en· W4408578495 on OpenAlexafffund
Md Washim Akram, Huiqing Guo, Wenbin Hu

Bibliographic record

VenueEnergy and Built Environment · 2025
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsFactory (object-oriented programming)Computer simulationEnvelope (radar)Mining engineeringBuilding envelopeHeat transferGeotechnical engineeringGeologyEngineeringEnvironmental scienceMechanicsComputer scienceMeteorologyAerospace engineeringSimulationGeographyPhysics

Abstract

fetched live from OpenAlex

• Conventional plant factories are energy intensive and affected by surface climate. • Underground mine tunnels provide suitable environmental conditions for plant growth. • Rock envelope reduces HVAC loads of underground plant factories (UGPF). • No research exists on heat transfer through surrounding rock envelope of the UGPFs. • This study developed a transient heat transfer model to predict HVAC loads in UGPF. Conventional plant factories (indoor vertical farming) are energy intensive and affected by surface climate whereas underground mine tunnels have a stable environment, and heat transfer through the surrounding rock envelope is expected to reduce cooling and heating loads of the environment control systems of the plant factories. The aim of this study is to numerically analyze short and long term heat transfer through the surrounding rock envelope for an underground plant factory (UGPF) located in a mine tunnel using ANSYS Fluent software. The model is compared with analytical results with discrepancies of 2.5 and 2.7 % for light and dark periods, respectively, indicating the numerical model is acceptable for further utilization in thermal modeling of the UGPF. For the base case of 284 K virgin rock temperature, 2.75 W/m.K rock thermal conductivity, 303 and 297 K indoor air temperature in light and dark periods, the time weighted average overall heat transfer coefficient is high initially with 4.04 W/m 2 ·K, but reduces rapidly in the first 6 months to 0.75 W/m 2 ·K, then slows down to 0.48 W/m 2 ·K in 3 years when the system almost reaches the equilibrium status. The heat transfer rate and overall heat transfer coefficient reduction with time follow power relationships. The results indicate that long term heat loss to rock envelope instead of initial values should be used in determining the cooling capacity of the plant factory considering the worst-case scenario. The sensitivity analysis shows that the rock thermal conductivity is more influential on heat transfer rate than indoor air temperature and virgin rock temperature, the latter two have similar levels of influence.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.214
Teacher spread0.198 · 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
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

Citations3
Published2025
Admission routes2
Has abstractyes

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