Least-Construction-Cost Approaches for New Housing to Achieve Higher Energy-Efficiency Requirements of Building Codes
Bibliographic record
Abstract
Effective November 1, 2016, new homes constructed in Alberta, Canada, are required to comply with “Section 9.36: Energy-Efficiency Requirements” of the Alberta Building Code (ABC) 2014. This section introduces ~57% stricter energy requirements for building envelope than the previous code; therefore, it is important to investigate its implications on current housing construction practices and energy performance, and to develop a methodology for selecting cost-effective approaches for code compliance. In this context, this thesis investigates the mentioned code and codes from other countries in cold-climate regions, identifies the current common practices, develops least-construction-cost approaches to meet the code’s energy requirements, and assess the lifecycle economic performance of a code-compliant house. Three approaches for code compliance are developed in this thesis: (1) least-construction-cost upgrades for building envelope (attic ceiling, above- and below-grade walls, and windows) meeting code-specified thermal insulation values specified in the prescriptive path of the code; (2) carry out approach (1) with energy-efficient tankless domestic hot water system and optimal window sizing for less lifecycle operation cost; and (3) least-construction-cost upgrade for the performance path of the code. To perform this assessment, a 30-year lifecycle analysis is conducted using HOT2000 simulations to estimate the energy performance and operation cost of a home Edmonton. By deploying approach (1), a reduction of ~12% on energy consumption is achieved with a return on investment (ROI) of ~ −3.44%. By applying approach (2), a reduction of energy consumption of ~27% is obtained with an ROI of ~68.08%. Alternatively, in approach (3), a reduction of energy consumption of ~10% with an ROI of ~527.21% is achieved. By applying the methodology developed in this research, least-construction-cost code-compliant upgrades are easily identified for other climatic conditions and Canadian locations.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".