Bibliographic record
Abstract
Globally, residential electricity consumption for space cooling is projected to increase by a factor of 40 over the course of the 21 st century.Given that 66.8% of worldwide electricity is generated from the combustion of fossil fuels, a surge in air conditioning of this magnitude would add millions of tonnes of carbon dioxide to the atmosphere annually.The extent of these emissions can be reduced by upgrading the energy efficiency of the existing air conditioner stock, by employing more stringent building energy codes, and by implementing energy conservation programs.However, the most effective mitigation strategy may be the widespread adoption of alternative cooling technologies that consume considerably less electrical energy.One such technology is the sorption chiller, which can be driven by lowgrade heat provided by solar thermal collectors.Although residential solar-driven sorption chillers have gained popularity during the past decade, there exist approximately only 1000 worldwide installations today.The unique nature of each system (i.e., local climate, solar collector size/type/orientation, utilization of thermal storage, operating strategy) makes it difficult to extend the performance of existing installations to future projects.Therefore, before widespread implementation of this technology can occur, more work is required to adequately model the performance of the current generation of commercially available sorption chillers over their full range of operating conditions.This thesis presents the experimental testing results of a novel triple-state sorption chiller with integrated cold storage.The performance of the chiller was measured for hot water inlet temperatures between 65°C and 95°C, heat rejection inlet temperatures between 15°C and 35°C, and chilled water inlet temperatures between 10°C and 25°C.The performance data collected
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".