HVAC solutions and energy systems for high performing buildings
Bibliographic record
Abstract
Under the pressure to achieve the goals set by the “20-20-20 target”, European countries must find efficient ways to cut down energy consumption in all sectors of society. The building industry accounts for over 40% of the total EU energy consumption and 36% of CO2 emissions and therefore it is an area of great potential. Initiatives like the EPBD recast oblige member states to push towards making new and existing constructions net-zero energy buildings (NZEBs). Annex 59 of the ECBCS arises from the need to investigate HVAC solutions for high performing buildings. Itsgoal is to analyse the impact of high temperature cooling and low temperature heatingon energy consumption. The investigation process in this thesis involved the modelling and modifying of a stateof-the-art Canadian NZEB with DesignBuilder. Changing the dwelling’s HVAC system, and taking into account a recently developed concept called ‘entrasy’, it was possible to demonstrate that high temperature heating and low temperature cooling HVAC systems decrease energy consumption considerably.
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 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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".