Shading and Air Flow Analysis on Selected Residential Buildings in Al-Bayda City, Libya
Bibliographic record
Abstract
A lot of energy is required to provide a comfortable interior with air conditioning systems. The use of high energy in buildings has made an essential contribution to climate change and air pollution. It is crucial for energy efficiency to reduce energy consumption. Applying the architectural principles of climatic design can provide thermal comfort in residential buildings. In this research, an analytical study was conducted on the climate factors that affect the energy consumption in the residential buildings in Al-Bayda, Libya. Eight buildings were randomly selected. The impact of solar energy, orientation, and wind factors that affect the climatic comfort on the selected residential buildings were considered as the leading indicators for improving energy consumption. These topics were studied comprehensively on the chosen buildings, and outcomes of the analysis were evaluated. Users gave answers to the questions regarding energy consumption, protection and utilization from the sun and air currents, and the physical insulation status of the building during the interviews. Independently of these, the results of airflow and shade analysis based on theories of passive design principles for each building have been revealed. It was observed that the answers of users and analytical results were consistent with each other. In the end, simple constructional applications that can prevent high energy use were recommended for future architectural designs. In this way, extensive use of air conditioners and thus air pollution, which has become one of the significant problems in Libya's cities, can be reduced to a certain extent.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".