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An analysis of the accuracy and computational efficiency of the use of one-dimensional fluid models in borehole heat exchangers

2025· article· en· W4409448250 on OpenAlexafffund
A. Holmes, C. Millar, M.F. Lightstone

Bibliographic record

VenueGeothermics · 2025
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoreholeHeat exchangerGeologyPetroleum engineeringThermodynamicsGeotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

• Novel methodology of modelling borehole heat exchangers to reduce computational time within COMSOL Multiphysics. • Symmetry planes with equation adjustments implemented with one-dimensional linear fluid elements to provide accurate results and reduced computation efforts. • Comparison of full three-dimensional CFD model in ANSYS CFX solving Navier-Stokes and energy equations within the fluid. • Models validated with experimental thermal response test data. This paper compares the accuracy of a one-dimensional fluid model to that of a fully three-dimensional model for the simulation of a thermal response test performed on a single borehole heat exchanger. The simplification of the fluid domain within the one-dimensional model allows for reduced computational time while still maintaining an accurate prediction of transient fluid temperature. The model uses a simplified one-dimensional fluid model while solving the full three-dimensional transient heat conduction equations in the borehole heat exchanger and surrounding ground. A symmetry plane is implemented to further reduce the computational effort, and the model and equation adjustments necessary to merge the use of symmetry planes and 1D linear elements along the central plane without loss of model accuracy is explained in detail. The proposed model is compared to a full CFD model and validated using experimental data for a constant heat rate test, commonly known as a thermal response test, to ensure no accuracy is lost due to model adjustments. Additionally, the computation times are compared for each case to quantify the time savings that result from model implementation.

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)0.001
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.029
GPT teacher head0.255
Teacher spread0.227 · 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
GenreMethods

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

Citations10
Published2025
Admission routes2
Has abstractyes

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