Experimental Results of a Solar Thermal System with Sensible Storage in a Single Family Residential House
Bibliographic record
Abstract
Solar thermal systems with diurnal and seasonal storage in residential buildings present a significant opportunity to satisfy space heating and domestic hot water heating loads and reduce fossil fuel consumption.This research focused on the operation and maintenance of a solar thermal system with sensible water-based diurnal and seasonal storage at the Centre for Home Energy Research (CHEeR) in Ottawa Ontario, Canada.A one year long experiment spanning from June 1, 2022, to June 1, 2023, was conducted to determine the solar thermal systems' effectiveness at supplying space and domestic hot water heating using stored solar thermal energy.The solar collection system consisted of a 41.6 m 2 array of high-performance heat pipe evacuated tube solar collectors.The diurnal storage that satisfied domestic hot water demands was a 450 L water tank in the basement of CHEeR.The seasonal thermal storage that served space heating demands via an in-floor radiant heating system was a 36 m 3 storage tank located underground adjacent to CHEeR.The solar thermal system supplied 81.0% of the domestic hot water loads and 87.5% of the space heating loads.Overall, when accounting for pump electrical energy consumption the system operated at a net overall solar fraction of 78.8%.i amazing support when something at CHEeR broke.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".