Towards Sustainable Building Design: The Impact of Architectural Design Features on Cooling Energy Consumption and Cost in Saudi Arabia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Energy-saving has become a high priority in the Architectural design of buildings, particularly in hot climate regions like Saudi Arabia. Thus, selecting the appropriate Architectural Design Features (ADFs) at the early design stage provides significant opportunity to manage heat flow, prevent excessive energy consumption, and maintain a comfortable temperature for the occupants. In this research, a structured “Architectural based-Energy Impact Scoring System (AEISS)” has been developed. The system incorporates seven key ADFs that were identified based on inputs from a large number of experienced architects, and embody 40 different design options. To support designers in selecting and evaluating, including energy analysis, of any Architectural design that has any combination of design options, AEISS incorporates a comprehensive decision scoring system. Energy analysis is performed using a simulation tool (Ecotect®) that is integrated with the Revit BIM models. To validate AEISS, three design alternatives were evaluated for a residential building in Saudi Arabia. Using AEISS, it was possible to arrive at the optimum design. This research presents a scientific decision-making approach to quantify design alternatives while reducing designers’ subjectivity in the evaluation process.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it