Drain Water Heat Recovery: in-situ data: quantifying the impact of plumbing configuration on the overall performance
Bibliographic record
Abstract
Drain water heat recovery heat exchangers are employed to capture thermal energy from water flowing down drain stacks in residential buildings. This technology is crucial for designers aiming to enhance energy efficiency in Canadian homes, with NBC Tier 5 energy performance being significantly challenging without it. However, understanding and addressing the nuances in the performance of this technology is essential. This report investigates how different plumbing configurations affect the same heat exchanger while maintaining a consistent flowrate and temperature at the showerhead. Essentially, it measures the in-situ impact of plumbing configurations on the heat exchangers' performance, providing valuable insights for designers and codes committees to make informed decisions regarding this technology. Findings reveal that plumbing configurations greatly affect heat exchanger performance, with each configuration offering distinct advantages. The results showed that the energy savings associated with the same shower event could differ by more than 30% for the most and least effective configurations tested in this work. Notably, the greatest savings come with the highest penalty (i.e., pressure drop), and the most efficient setup might not always be the best fit for a specific dwelling. This decision is highly dependent on the plumbers' preferences and priorities. The report discusses metrics such as 1) energy saving, 2) pressure drop, and 3) legionella potential, advising codes committees to consider all these factors, which are influenced by the home's plumbing configuration, regardless of the installed heat exchanger.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".