Underground Energy Storage Utilizing Building Concrete Foundation with PCMs: Experimental and Numerical Approach
Bibliographic record
Abstract
<p>Geothermal energy utilization has increased 90 times since 1995 [1], ground source heat pump (GSHP) has the largest share of this value in a way to reduce the burning of fossil fuels and contributing to the reduction of greenhouse gases (GHG) emissions. Space requirement and the high initial cost of borehole field hinder the widespread of GSHP. Building foundation piles as a GHE has been presented to eliminate these limitations. However, the foundation piles have a lower depth and small spacing compared to the borehole. To increase the storage capacity and to decrease the thermal radius of energy piles, phase change material (PCM) has been presented as a potential solution. In the current study, laboratory-scale energy piles were built with and without PCM, along with a 3-D finite element model. The numerical predictions were validated with the experimental measurements, allowing the investigations of more parameters numerically. The experimental and numerical results showed that PCM increased the storage capacity and decreased the temperature distribution of the lab-scaled pile. The validated model was then modified to study the effect of latent heat and melting temperature numerically. Increasing PCM latent heat increased the models’ storage capacity and decreased their temperature distribution. The validated numerical model was then scaled up to simulate an actual energy pile with a depth of 25 m and a diameter of 1.5 m. The pile’s performance was investigated with an actual building load for a complete year. While the actual heat pump performance curve was integrated into the numerical model. PCM enhanced the heat pump coefficient of performance (COP) by up to 5.2% during the melting of PCM, while its low thermal conductivity decreased the COP by up to 1.8% during the complete solid state. PCM cylinders’ location was also investigated at 6 different locations. In addition, two PCM melting temperature ranges were investigated in order to determine the effect of PCM melting range, the results showed that PCM with a melting temperature range of (4-6)°C is better than a melting range of (1-3)°C for the current study load. Finally, two different PCMs were used inside the same energy pile along the symmetry lines, which showed an average enhancement of 9%.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".