Continuous Model Simulations to Develop a Phased Approach for SSO Control in Piqua, Ohio
Bibliographic record
Abstract
The City of Piqua, Ohio, initiated a study to develop an alternative for meeting regulatory requirements regarding an active sanitary sewer overflow (SSO) in its wastewater collection system. Continuous hydraulic model simulations were used to study how to reduce the frequency of the city's SSO. The U.S. Environmental Protection Agency's Storm Water Management Model (SWMM) version 5 built upon the city's existing model and validated the model based on reported annual SSO activity using continuous simulations. The city's collection system includes 192 km sanitary sewers. The city's wastewater treatment plant (WWTP) accepts an average flow of 175 L/s. Five-year continuous simulations were used to assess performance of an alternative that included an equalization (EQ) basin to store excess wet weather flows (WWFs) to greatly reduce SSO. The modeling identified existing system hydraulic capacity limitations and helped to optimize the EQ basin alternative. Optimization included using the model to identify an EQ basin location that uses gravity-in/gravity-out operation, minimizing infrastructure modifications. The continuous simulation approach resulted in a phased alternative and corresponding conceptual design that will provide the city with flexibility in controlling SSO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".