Abstract
Large-scale combined sewer systems are susceptible to overflows (CSOs) during heavy storm events. Management strategies that partition water flow into the sewers or nearby waterways may be based on conservative operational rules designed to prevent possible flow instabilities. However, these operations may not effectively utilize system storage capacity for all types of storm events. Real-time adaptation of system operating rules can reduce overflows while continuing to avoid hydraulic conditions that lead to transients and geysers. In this study, realtime genetic algorithm (GA) optimization is evaluated for its success in minimizing CSOs for a test case modeled after a portion of the Chicago Tunnel and Reservoir Plan (TARP).
| Original language | English |
|---|---|
| Title of host publication | World Environmental and Water Resources Congress 2011 |
| Subtitle of host publication | Bearing Knowledge for Sustainability - Proceedings of the 2011 World Environmental and Water Resources Congress |
| Pages | 2911-2919 |
| Number of pages | 9 |
| DOIs | |
| State | Published - 2011 |
| Event | World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability - Palm Springs, CA, United States Duration: 22 May 2011 → 26 May 2011 |
Publication series
| Name | World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability - Proceedings of the 2011 World Environmental and Water Resources Congress |
|---|
Conference
| Conference | World Environmental and Water Resources Congress 2011: Bearing Knowledge for Sustainability |
|---|---|
| Country/Territory | United States |
| City | Palm Springs, CA |
| Period | 22/05/11 → 26/05/11 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Decision support systems
- Overflow
- Sewers
All Science Journal Classification (ASJC) codes
- General Environmental Science
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