Four Large Units at Lakeview Generating Station Achieve 50% NOx Reduction Cost Effectively With a Reduced Schedule
Bibliographic record
Abstract
As part of a much larger Ontario Power Generation NOx reduction program, two separate turnkey contracts were awarded to RJM Corporation to convert the four units at the Lakeview Generating Station located on lake Ontario near downtown Toronto. Lakeview Station Units 1, 2, 5 and 6 are 300 MWe, B&W split furnace, radiant boilers firing bituminous coal. Units 1 & 2 have 24 burners and Units 5 & 6 have 18 burners all located on the front wall. The original B&W register style burners were used as a basis to reduce NOx emissions to the maximum amount possible by means of burner modifications using RJM’s low NOx burner components. This upgrade reduced NOX by more than 50% from the original burner baseline, simultaneously maintained CO below 100 ppm and maintaining a reasonable increase in baseline LOI, with no effect on boiler steam temperatures or performance. RJM Corporation was selected on a competitive bid basis to perform these contracts on a turnkey basis. Stone and Webster prepared the specification and acted as the OPGI engineer throughout the project. The details of the retrofit and the results of the conversion are presented in this paper.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.009 |
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".