The possibility to lower building energy consumptions in Qatar
Bibliographic record
Abstract
Most global energy comes from fossil fuel. Currently, there is a strong belief that climate change is anthropogenic and attributed to fossil fuel consumption. Heating and cooling systems account for half of global energy consumptions. In hot and underdeveloped countries such as Qatar, the share of air conditioning systems is expected to be even more than half the national energy consumption. This provides the challenge to study energy consumption in building sectors to find new methods to increase the performance of air conditioning systems. Up until now, renewable energy sources supply only around 2-3% of the annual global heating and cooling demand. Due to its high thermal performance, heat pump systems and in particular ground coupled heat pump systems (GCHP), are increasingly becoming more common for air conditioning applications. In the light of the improvement in performance of photovoltaic systems, the combination between the photovoltaic and HP or GCHP is gaining more economic feasibility. This paper studies renewable energy options for building cooling systems for energy and environment savings. To achieve this goal, a residential apartment in Doha, Qatar, was selected as a case study. The cooling demand of the case study was assessed and four different cooling systems were designed including: (1) air coupled heat pump system (as a reference system); (2) ground coupled heat pump; (3) air coupled heat pump combined with a photovoltaic panel to generate electricity; and (4) ground coupled heat pump combined with a photovoltaic panel to generate electricity. Compared to the reference system, the reduction in the non-renewable energy consumption and the payback time was estimated for each system.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".