Energy Efficiency Measures Applied to Heritage Retrofit Buildings: A Simulated Student Housing Case Study in Vienna
Bibliographic record
Abstract
One pavilion was selected for deep retrofitting from the Otto Wagner area situated in the west of Vienna. The retrofitting process involves sustainable and energy-efficient construction to improve the energy performance and energy production potential of the building while preserving the cultural heritage and significance. This four-story pavilion was re-designed according to the proposed regulations of a net positive energy university building to become a student residence. Architectural, building envelope, and engineering interventions along with various changes were simulated through the Sefaira tool in the SketchUp model. These included: optimization of the U-values of the roof, walls, and floor; the addition of different layers of sustainable energy-efficient insulation materials to decrease the overall energy demand. The specific energy demands for heating, cooling, and lighting were decreased in the proposed model to reduce the total energy use intensity from 248.9 kWh/(m2 year) to 54.3 kWh/(m2 year) resulting in a 78.2% reduction. The main goal of this study is to try and achieve a net positive energy status building as part of the Otto Wagner area by improving the building envelope and integrating renewable energies. A total of 22.5% of the annual energy consumption was generated by the designed PV system. The selected building achieved the passive house standards in Austria by optimizing the energy performance with the proposed energy efficiency measures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".