Design and Commissioning of an Experimental Set-Up to Evaluate the Performance of a Solar Absorption Chiller With Thermal Storage
Bibliographic record
Abstract
As the demand for cooling increases in Canada, it creates a greater energy demand on the utility grid by placing peak loads during the summer months. As a result, air conditioning in the residential sector is responsible for a disproportionately large and increasing amount of CO2 emissions in Canada. One potential solution is the use of solar thermally driven absorption chillers, however before their widespread use in Canada is possible, extensive testing and optimization of the systems must be conducted to determine their feasibility in the Canadian climate. This paper discusses a full scale experimental test rig that has been recently constructed and commissioned to experimentally evaluate the performance of a commercially available solar absorption chiller with integrated thermal storage. The complete system is described, including the system’s test capabilities, the instrumentation installed, the control system developed, and the calibration and uncertainty analysis completed on each individual sensor and the system as a whole. Additionally, the paper examines the charge cycle of the solar absorption chiller being studied, and compares the results to simulation results obtained from a TRNSYS model of the test apparatus.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".