Bibliographic record
Abstract
Ground source heat pump (GSHP) systems are an increasingly attractive option for reducing building energy use and emissions. These systems rely on ground heat exchangers (GHEs) that act as both heat sinks and heat sources, and accurate GHE modeling is necessary for reliable design. Determining the size of the GHE required to meet design requirements is a critical aspect of GSHP system design. The purpose of this study is to advance GHE design methods through the development, refinement, and validation of new modeling capabilities within GLHEPro Version 5.1, together with improvements to g-function generation and handling. GLHEPro has long been used for vertical closed-loop GHEs, but emerging applications such as standing column wells (SCWs) and non-conventional borehole systems, along with increased usage of deep borehole GHEs, necessitated further development of the design tool. A central contribution is an improved, computationally efficient model for SCWs. The groundwater-filled borehole is represented by a single control volume surrounded by a one-dimensional radial finite volume grid that captures both conduction and pumping-driven advection, while buoyancy effects are represented through an enhanced effective thermal conductivity. A user-specified large fracture flow fraction (LFFF) parameter allows part of the flow that enters back into the borehole to be through large fractures, bypassing the surrounding rock. The model is validated against a 35-day summer multi-flow-rate thermal response test and a 25-day winter operation test from a field installation in Varennes, Canada, yielding mean absolute errors in SCW outlet temperature of 0.32 °C and 0.68 °C, respectively, with more than 70% of the hours falling within experimental uncertainty. Several advancements in g-function handling were implemented. Short-time-step (STS) g-functions were reformulated to utilize effective pipe and grout resistance when the user chooses to consider thermal short-circuiting, removing discontinuity between STS and long-time-step (LTS) g-functions. Interpolation strategies were introduced for both single and multiple boreholes to improve accuracy across a wider range of borehole geometries. A user-specified borehole resistance option was added so users can anchor their borehole behavior to their estimated or manufacturer specified resistance values, while retaining the internal transient solution structure. This enabled modeling of custom non-conventional boreholes in GLHEPro. Additional enhancements include a more robust iterative solver enabling sizing of deep boreholes, and support for ground loads in both hybrid sizing and hourly simulations. Validation against four field installations showed borehole sizing results within 17% for cases with adequate flow rate, which is reasonable when considering the accuracy limits of the hybrid time-step method and other underlying conservative assumptions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".