A Framework for Energy and Thermal Performance Modeling in Net-Zero Urban Clusters
Bibliographic record
Abstract
This study presents a data-driven framework for optimizing net-zero building design by integrating urban context, building form, and façade configurations. Using parametric modeling, genetic optimization, and empirical validation, it examines energy performance across the building-height-to-street-width ratio, number of floors, aspect ratio, floor area, window-wall ratio, and photovoltaics’ tilt angle. Results indicate that context compactness increases heating demand by 2.1 kWh/m2 (0.195 kWh/ft2) and reduces cooling demand by 1.8 kWh/m2 (0.167 kWh/ft2) per incremental increase: higher floor area and building height enhanced energy efficiency. Building height marginally influenced heating and cooling for an aspect ratio above 5, peaking at 4. Façade-based production escalated by 10,000 kWh per unit after the aspect ratio exceeded 2. Photovoltaics’ tilt angle significantly impacted consumption and production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".