Increasing efficiency of the University of Calgary's cogeneration plant by capturing surplus heat
Bibliographic record
Abstract
This study explores the feasibility of installing a new electricity generation technology that utilizes the surplus heat that exists today at the University of Calgary’s cogeneration power plant during the warmer months periods. Using historical data from the cogeneration power plant, heating needs from campus buildings and 30-year average weather data, the available resource is calculated allowing to choose a technology that is capable of generating electricity taking advantage of that heat energy. Organic Rankine Cycle electricity generation was chosen for its versatility and ability to generate electricity from low to medium heat sources. Considering the resource available, the costs of purchase and installation and the capacity four IT 250 ORC generator have, a payback period of 14 years expected as well as a Scope 2 emissions reduction of 1,230 tonnes of CO2 per year allowing the University to move forward with its climate action plan that seeks to propel the University as a leading educational institution in sustainability, innovation, and climate action with the final goal of being net-zero by 2050.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".