Sensitivity Analysis of Two Solar Combisystems Using Newly Developed Hot Water Draw Profiles
Bibliographic record
Abstract
This research addresses the viability of two solar combisystems, which use solar energy to provide both space heating and domestic hot water, for several single family homes in Ontario.Hot water use data from seventy three homes were refined to create twelve different draw profiles representing a variety of consumers.These profiles were divided up based on the magnitude of daily draw and the preferred time of use.It was determined that time of use had little to no effect on performance.However, the magnitude of a daily draw was seen to have a significant effect on the final energy use of a home.Two different combisystem plant configurations, a single tank system and a two tank system, were simulated.It was determined that the single tank system offered superior performance.Unless systems were sized to the upper limits tested here, a solar fraction of 50% could not be achieved.iii I would like to first thank my supervisor, Dr. Ian Beausoleil-Morrison.Your knowledge and advice could not have been more useful.My appreciation to my friends and colleagues: GJ, PP, AW, SB, JK, SM, BPK, and SH.You were always there for
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".