Evaluation of mixed mode ventilation cooling energy saving potential in nZEB: A case study in Southern Italy
Bibliographic record
Abstract
In recent decades, reducing the energy demand of the building sector has become a major goal of global policies. Proper design of the building-plant system is hence strategic to achieve nearly zero energy building (NZEB) target. This paper reports the results of modeling the building-plant system of an NZEB in Southern Italy. The case study is a multi-family complex of eight dwellings located in Bari, in the Apulia region. The building project originates from the energy refurbishment of a former industrial shed that was demolished and rebuilt for residential use. The planned HVAC system foresees the combined use of primary ventilation with fan-coil units fed by two ground source heat pumps (GSHP) supplied by eight vertical probes. Three hybrid ventilation strategies have been compared to evaluate the potential cooling energy saving: the first one examines an earth-to-air heat exchanger (EAHX), the second one proposes night hybrid ventilation from 10 pm to 6 am, and the last considers the adoption of free cooling in mechanical ventilation. Economic and energy comparisons among these three approaches are reported. Using EAHX, the cooling consumption saving reached about 20.7% The use of night ventilation combined with MVS can reduce the cooling energy demand for 14.4%, while free cooling in MVS produces a less effective decrease in the electricity consumption for cooling of about 7.7%. All three strategies generate major benefits in the middle-season.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".