Application of PCM in a Zero-Energy Building and Using a CCHP System Based on Geothermal Energy in Canada and the UAE
Bibliographic record
Abstract
In this research, the optimization of energy consumption of zero-energy buildings using PCMs in the two study cities of Vancouver and Dubai and its energy supply with a multi-generation geothermal system is discussed. PCMs used in the walls and roofs of designed buildings are of two types, namely PCM (solid) and PCM (liquid). By optimizing the energy consumption of the residential complex in two study cities, it is finally possible to choose the best mode in optimal conditions to reduce energy consumption in the residential complex, reduce the costs of the residential complex, and reduce the environmental pollution. The results showed that the amount of electricity consumption, heating, and cooling of the residential complex during the year in the city of Vancouver is 8493.55, 7899.1, and 1083.97 kWh, respectively, and in the city of Dubai, the values are 9572.1, 8.99, and 18,845.44 kW, respectively. Also, by optimizing the energy consumption of residential complexes in Vancouver and Dubai, it is possible to reduce CO2 emissions by 2129.7 and 2773.2 kg/year, respectively. The electricity consumption of the residential complex in Dubai is 11.26% and the carbon dioxide emission is 23.20% more. In the end, a multi-generation system is proposed to meet the energy consumption of a six-unit zero-energy residential complex with 120 m2 and two bedrooms in Vancouver, Canada. By setting up the study system in the city of Vancouver, 237,364.6 kWh of electricity, 425,959.4 kWh of heating, and 304,732.8 kWh of electricity can be produced in one year. According to the investigation, the geothermal system can easily provide the energy consumption required by residential buildings.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".