Abstract
AbstractAn approach that links genetic algorithm (GA) as an optimization tool with Monte Carlo simulation (MCS)‐based reliability program is presented for reliability‐constrained optimal design of water treatment plant (WTP). The reliability of a WTP is defined as its ability to produce water of desired effluent water quality standard. The objective function minimizes the treatment cost subjected to reliability constraint, design constraints, and performance constraints. The random variables used to generate the reliability estimates are suspended solid concentration, viscosity of water, specific gravity of floc particle, sedimentation basin performance index, velocity gradient, and flow rate. The application of GA‐MCS approach for design of a WTP is illustrated with a hypothetical case study. The application shows that the reliability of achieving desired water quality standard is affected by the uncertainty of system parameters. The suggested GA‐MCS approach is efficient to evaluate treatment cost‐reliability tradeoff in design of WTP. © 2008 American Institute of Chemical Engineers Environ Prog, 2008
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
