Modelling real-time control options on virtual sewer systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study presents a benchmarking methodology to assess the performance of sewer systems and to evaluate the performance of real-time control (RTC) strategies by model simulation. The methodology is presented as a general stepwise approach. Two virtual sewer systems were modelled under four climate conditions. Catchment A represents a small system with medium RTC potential, while catchment B represents a large system with large potential according to PASST guidelines. The rain data represented Oceanic, Continental, Alpine and Mediterranean situations. Annual precipitation data was used. Tests included operation without RTC, and with two classic RTC strategies, aiming at, respectively, equal filling of storage tanks (“average filling”), and aiming at avoiding spilling just upstream of the treatment plant (“WWTP load”). The results have shown that similar RTC strategies perform differently under various climatic conditions and in sewer systems. The presented benchmarking methodology can be used to test the impacts of various climate scenarios on sewer systems that suffer from the limitations of static design.
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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 | 0.000 | 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 | 0.001 |
| 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 it