Life‐cycle energy analysis of performance‐ versus age‐based pipe replacement schedules
Bibliographic record
Abstract
Although many North American water utilities are upgrading their systems through both regular maintenance programs and additional pipe replacement, rarely does this process take whole‐of‐life considerations into account. This article details the development of a life‐cycle energy analysis that accounts for energy associated with reducing leakage through pipe replacement and describes its implementation at a large water distribution system. Energy used in pumping was compared with the embodied energy tied to pipe replacement in a baseline scenario and three replacement plans. Results indicated that the annual operational energy savings of 4.9 × 10 to 6.4 × 10 kW·h achieved by 2020 comes at a cost. The embodied energy invested in replacing pipe stock for ductile‐iron pipes with diameters of 6 to 16 in. would be 0.88 × 10 to 2.05 × 10 kW·h/mi, a significant expense that results in an initial energy payback period of 17.6 years for the most aggressive replacement plan.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".