Investigative approach to improve hot water system hydraulics through temperature monitoring to reduce building environmental quality hazard associated to Legionella
Bibliographic record
Abstract
Several countries have promulgated control measures and design guidelines to limit the proliferation of Legionella within hot water distribution systems (HWDS). However, there is little information on how to assess and improve existing HWDS unable to maintain water temperatures ≥55 °C throughout the system. A 50-year old hot water system of a 10 story hospital was investigated in terms of temperature distribution and Legionella pneumophila prevalence. Concentrations of L. pneumophila were correlated with the maximum temperature reached at the tap, with a significant decrease observed at T ≥ 55 °C. Continuous temperature and flow monitoring was performed on the overall HWDS, characterizing the principal and secondary horizontal return loops for all 9 wings, and detailed investigations of the secondary vertical return loops was completed in Wing 3. Results indicated the system inability to systematically maintain desired operating temperatures of 55 °C. The deficient hydraulic distribution was the root cause of the poor temperature maintenance throughout the secondary loops, but defective devices were also identified as playing an important role in sectorial temperature failure. A simple stepwise investigative approach was developed to identify hydraulic deficiencies. The implementation of flow restrictions on identified recirculation loops and increased pumping efficiency was conducted within a short period of 2 months, with no major system upgrade. These corrective measures resulted in a balanced system with increased flow velocities (>0.2 m/s). As a result, the proportion of taps achieving 55 °C within 2 min increased from 11% to 74% and L. pneumophila prevalence decreased from 93.1% to 46.1% after 4 weeks.
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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) | 0.000 | 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 | 0.001 |
| 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".