Modelling and Simulation of Seasonal, Solar Driven Sorption Thermal Energy Storage in Cold Climate Residential Application
Bibliographic record
Abstract
In this study, a sorption thermal energy storage system was modelled in TRNSYS and integrated with existing building performance models of a single-detached residential dwelling equipped with an array of evacuated-tube solar thermal collectors in Ottawa, Ontario. The proposed sorption system consists of a closed, modular reactor and uses a lithium chloride composite-salt-in-porous-matrix/water working pair and an idealized evaporative heat source. Results of a parametric study found that an overall solar fraction of 90% could be achieved for an energy efficient house with 2000 kg of sorbent material and a total system volume of 9.3 m3, and a 95.4% overall solar fraction could be achieved with 3000 kg of sorbent and a total system volume of 25.3 m3. The sorption system was able to reduce the space and water heating demands by as much as a 42.1 m3 sensible STES while taking up only 60% as much volume.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".