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Record W7124537499 · doi:10.15377/2409-5818.2025.12.3

Experimental Evaluation of a Simulated Geothermal Heat Pump System for Potential Large-Scale Space Heating Application at TBRHSC in Severe Cold Climate in Northwestern Ontario, Canada

2025· article· W7124537499 on OpenAlexafffundabout
Basel I. Ismail, Anjali Nagi

Bibliographic record

VenueGlobal Journal of Energy Technology Research Updates · 2025
Typearticle
Language
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsLakehead University
FundersGoldcorpLakehead UniversityNorthwestern University
KeywordsThunderHeat pumpRenewable heatHeating systemGeothermal gradientEnergy consumptionThermalThermal comfortAir source heat pumps

Abstract

fetched live from OpenAlex

Space heating for buildings and institutional complexes represents a dominant sector of energy consumption and greenhouse gas (GHG) emissions in Canada, a challenge exacerbated by the nation’s cold climate. This is particularly critical in regions like Thunder Bay, where harsh winters and significant heating demands make the building sector a major contributor to local emissions—the residential sector alone accounts for 27% of community GHG output. The geothermal heat pump (GHP), or ground-source heat pump, is a highly efficient technology that leverages the stable thermal energy of the subsurface to provide space conditioning. By using the ground as a heat source in winter and a heat sink in summer, GHPs can reduce heating and cooling energy use by 25–50% compared to conventional systems. This makes them a promising solution for large-scale space heating applications, such as at the Thunder Bay Regional Health Sciences Centre (TBRHSC), a major healthcare facility and one of the city’s largest energy consumers. Despite this potential, there remains a significant gap in region-specific performance data and operational understanding of GHPs in extreme cold climate in Northwestern Ontario. This study addresses that gap through experimental characterization of a lab-scale GHP system using actual subsurface temperature profiles. An extensively instrumented GHP simulator was employed to evaluate system performance across a key range of operating conditions. The experimental results showed that the supply air temperature from the GHP system rises rapidly following system start-up, with each tested condition achieving approximately 90% of its peak value within the first 4 to 5 minutes. A consistent thermal gain of the GHP was observed, where each 5°C increase in entering water temperature yielded an additional 3°C rise in the useful supply air temperature. The temperature gradients plateau after 10 min indicating that the system has achieved a thermal steady state. Progressively increasing the simulated ground-loop water temperature entering the GHP’s evaporator from 5°C to 10°C and then to 15°C resulted in a corresponding rise in supply hot air temperature and an improvement in the GHP system’s coefficient of performance (COP).

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.302
Teacher spread0.289 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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