Domestic Water Treatment Plant

Abstract

This Domestic Water Treatment Plant study presents an optimization framework for investigating the effects of five variable influencing parameters and three uncertain model parameters on low-cost plant configuration contact, direct, or non-sweep conventional filtration that reliably satisfies an effluent particulate matter concentration constraint.

The inclusion of variability and uncertainty can also result in a shift in the locations of the least cost configuration regions, which depend on the expected influential water quality and the magnitude of variability and uncertainty.

Additional information provided by incorporating variable and uncertain parameters shows that parameter distri-butions related to the primary removal mechanism are critical and that contact and direct filtration are more sensitive to variability and uncertainty than conventional filtration.

Conclusion

This study extends previous research on treatment plant design for particulate removal by developing a decision support tool that explicitly considers variability and uncertainty in the decision-making framework.

To develop robust designs, environmental process decision-making must include the inherent variability associated with environmental conditions and the uncertainty in the parameters used to describe critical processes in the model.

This study extends previous research on treatment plant design for particulate removal by developing a decision support tool that explicitly considers variability and uncertainty in the decision-making framework. The objective is to determine the appropriate low-cost treatment configuration contact, direct or conventional filtration while meeting multiple constraints, including meeting the restriction of effluent particulate concentration.