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 layout 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 m 3 , and a 95.4% overall solar fraction could be achieved with 3000 kg of sorbent and a total system volume of 25.3 m 3 .The sorption system was able to meet an equivalent fraction of the building's energy demands as a 42.1 m 3 sensible STES while taking up only 60% as much volume.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".