Energy Simulation of a Building Envelope for NetZero Energy Home (NZEH) Design
Bibliographic record
Abstract
Energy consumption due to residential building operation is a crucial issue in cold-climate regions. In order to alleviate the energy demand from residential building operation, the concept of NetZero energy homes (NZEHs) has emerged as a solution. Appropriate design of the building envelope for NZEHs, (including insulation type and thickness, configuration, and other parameters), is a key to ensuring a high level of energy performance of NZEHs, and energy simulation provides a tool to investigate the energy performance of design options for each component of the NZEH building envelope. HOT2000, which is a widely used energy simulation tool in Canada, is used for energy simulation in this research; in order to achieve the goal of simulation automation, the batch version of HOT2000 is utilized. The energy performance of design options is simulated for such main components of NZEH building envelope as main wall, exposed floor, attic, basement wall, and basement floor, and, based on the simulation results, the functions and charts of energy performance are developed for these components. This research contributes to the body of research in this area by analyzing the energy performance of design options for NZEH building envelope.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.005 | 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".