Analysis of natural gas consumption and energy saving measures for small and medium-sized industries in the greater Toronto area
Bibliographic record
Abstract
A total of 15 energy (natural gas) audits were conducted for industrial sites from food processing, packaged goods and finishing processes (powder coating) sector. Natural gas consumptions, performances of major gas consuming equipment and savings from proposed energy measures were analyzed for the audited sites. Proposed energy saving measures included reduction in non-productive consumption, tune-up of gas-fired equipment, optimization of boiler loads, heat recovery through feedwater economizer and reduction in oven exhaust using variable frequency drives (VFDs). Gas savings achieved by employing VFDs showed great potential ranging from 13% to 49% of oven consumptions while savings for feedwater economizer ranged from 3.4% to 18.4% of boiler consumptions. Other measures mentioned above, though relatively simpler to implement, also showed potential of considerable savings. Associated fuel cost savings and the reduction in greenhouse gas emissions were also estimated. Furthermore, a MATLAB program was created to calculate boiler efficiencies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".