Modeling of Seasonal Thermal Energy Storage Systems (STESs) with solar collectors
Bibliographic record
Abstract
These EXCEL file perform the numerical simulations of the annual evolution of an STES system (that is, the evolution of its temperature) based in a water tank and many solar collectors. This STES is heated by using the collectors ( (vacuum-tube or flat ones), which are characterized by its efficiency function. This system is simulated working on a house's roof in Bariloche (an Argentinean location) or Okotoks (Canadian location) in different files, but similarly, other locations could be simulated by using the right set of input parameters (climatic and solar ones). In this numerical code, these locations (and the yield of production for solar collectors there) are characterized by their average monthly solar factors and ambient mean temperatures. Besides, the water tank it characterized by means of its diameter (always using square cylinders, that is, having height equals to diameter), and overall thermal transmission coefficient (K, W/(m2.°C)), which determines the quality of its thermal insulation. This thermal modeling is based on some hypotheses: 1) The ambient temperature surrounding the water tank is uniform. This is reasonable for above-ground tanks (and especially for small tanks) as here is considered. 2) The temperature inside the water tank is uniform. this is reasonable for small tanks, especially aboveground ones, as here is considered. These data are fully related to the work entitled: HEATING HOUSES BY USING VACUUM-TUBE SOLAR COLLECTORS AND A SMALL ABOVEGROUND WATER TANK: A COST-EFFECTIVE SOLUTION FOR MARITIME CLIMATES what is been published in the journal: ADVANCED IN BUILDING ENERGY RESEARCH, of the Taylor & Francis Group And the solely author of this work is: Luis E. Juanicó juanico@comahue-conicet.gob.ar Instituto Andino Patagónico en Tecnologías Biológicas y Geoambientales (IPATEC) CONICET and National University of Comahue, (8400) Bariloche, Argentina
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".