The energy retrofit of building façades in 22@ innovation district of Barcelona: energy performance and cost-benefit analysis.
Bibliographic record
Abstract
Abstract Under the current Energy Performance of Buildings Directive, EU countries must set building energy renovation as a goal for future development of the cities. The 22@ district of Barcelona is one of the most thriving innovation districts of Europe with an increasing market for office buildings. In this framework, the present paper evaluates the effectiveness of a series of strategies considered the real case project of the energy retrofit of an existing building in 22@. In particular, the study presents the results of different scenarios of building retrofits, where simulations of dynamic envelopes are performed, with the inclusion of a conventional ventilated façade, Living Green Walls and Phase Change Material (PCM) for thermal energy storage. The different scenarios are compared in terms of energy performance, enhanced comfort and cost-benefit analysis. The benefits of latent thermal energy storage, improved thermal inertia and evapotranspiration of the vegetated elements are also assessed. Eventually this study helps understanding the feasibility of the implementation of the nZEB standard in energy retrofit of buildings in the specific context of Barcelona and Spain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".