Modelling of a Hybrid-Ventilated Building – Using ESP-r
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper reports the results of computer simulations of a hybrid-ventilated building using ESP-r (Environmental Systems Performance for research). A new school building in Norway was used for this simulation study. The research attempted to verify the use of this model for the simulation of a real building utilising hybrid ventilation technologies. The simulations and their analysis focus on the building’s thermal and ventilation performance.The model building has been simulated in three different categories: “building thermal simulation”, “air flow simulation”, and “building + air flow integrated simulation”. Measured weather data were used to define the outdoor conditions of the building.It covers a representative heating period comprising time-series of minutely measured values of air temperature, solar radiation, wind speed, and wind direction. In addition, to assist verification, some measured parameters of the indoor environment, such as temperature, were compared to model predictions.The research concludes that modelling of hybrid ventilated buildings using this type of approach is possible and the resultant outputs are feasible and practical in terms of both the thermal and ventilation points of view. However, at the same time, limitations do exist when it attempts to model complicated building systems or to model CO2 based control systems.
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.
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 it