Conference proceeding
OPTIMIZED DESIGN OF WASTEWATER DISINFECTION REACTORS BASED ON AN ARTIFICIAL NEURAL NETWORK METAMODEL
PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2016, VOL. 7
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Peracetic acid (PAA) is an emerging disinfectant for the treatment of wastewater. While it would be possible to optimize the design of this system using computational fluid dynamics (CFD), the computational intensity would be high. As an alternative, we show that an Artificial Neutral Network (ANN) based metamodel can approximate the CFD solutions over an 11 dimensional performance space (dimensions, hydraulic characteristics, and chemical kinetics). By sampling the design space using a quasi-random sampling technique, a series of CFD simulations of disinfection characteristics of PAA in a wastewater treatment reactor are carried out. After a training process using 40 different CFD runs are completed, the ANN developed can be used to achieve an optimized design of wastewater treatment facilities with minimal total cost and acceptable disinfection performance efficiency.
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Details
- Title
- OPTIMIZED DESIGN OF WASTEWATER DISINFECTION REACTORS BASED ON AN ARTIFICIAL NEURAL NETWORK METAMODEL
- Creators
- Wangshu Wei - Drexel Univ, MEM Dept, Philadelphia, PA 19104 USACharles N. Haas - Drexel UniversityBakhtier Farouk - Drexel UniversityASME
- Publication Details
- PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2016, VOL. 7
- Conference
- ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2016
- Publisher
- Amer Soc Mechanical Engineers
- Number of pages
- 8
- Grant note
- PeroxyChem LLC
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering; Mechanical Engineering and Mechanics
- Identifiers
- 991019170124704721
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- Web of Science research areas
- Engineering, Mechanical