Numerical evaluation of ground source heat pumps in a thawing permafrost region
Bibliographic record
Abstract
Permafrost degradation poses significant environmental and geological challenges in Arctic and subarctic regions, particularly in areas like Umiujaq, Canada. The warming climate leads to thawing permafrost, causing ground instability, disrupting hydrology, and impacting local built environment. This study evaluates the use of Ground Source Heat Pump (GSHP) operation for mitigating ground subsidence in a permafrost region using a two-dimensional Thermo-Hydro-Mechanical (THM) coupled finite element analysis considering the ground poro-elastic and poro-plastic responses. The research uses a single-well scenario to demonstrate the interactions among thermal, hydraulic, and mechanical processes. The impact of GSHP operation under different temperature management strategies, including a scenario with a constant GSHP temperature of −5 °C throughout the year is numerically investigated. Results indicate that GSHP operation exacerbates ground deformation near the borehole, particularly during winter months. However, maintaining GSHP operation throughout the entire year can mitigate extreme subsidence fluctuations, leading to a more stable subsurface environment. While GSHP systems provide effective thermal regulation, their operation can introduce mechanical stresses that potentially disturb the ground close to the borehole. Therefore, careful design, operation, and further research are essential to balance thermal benefits with ground stability in permafrost regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".