Evaluating Life-Cycle Energy Costs of Heritage Buildings
Bibliographic record
Abstract
After the sustainability of heritage buildings (HBs) has been evaluated and it is determined that rehabilitation is needed, then the life-cycle cost (LCC) of energy for HBs can be analyzed. The objective of this research was to evaluate the LCC of energy for HBs and develop a comprehensive life-cycle model that will aid in expenditure planning and budget allocation. This study was validated through the weighted sums method and two case studies—Murabba Palace (MP), Saudi Arabia; and Grey Nuns Building (GN), Canada—were evaluated. For any HB, the project life cycle includes planning, manufacturing, transportation, construction, operation, and maintenance phases. Saudi Arabian and Canadian experts completed questionnaires to attribute a percentage of importance of each of the aforementioned phases with respect to energy consumption. The findings from this study will enable facility managers to make effective rehabilitation decisions. The operation phase has the highest impact on the energy consumption, gas consumption, and cost of the building in both case studies. Moreover, the findings from this study can be used to establish cost-effective intervention strategies. Their responses were employed in the development of a life-cycle model. Excel® and Minitab® were used to calculate Cronbach’s alpha values for data reliability, and the project LCC of energy for the two case studies was studied. The operation phase appeared to be the most energy-consuming phase in both case studies, contributing the most to the cost of the building.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".