Houston, We Have A Solution: Enhancing The Water Digital Twin Using Machine Learning

How artificial intelligence is assisting the digital twin to benefit Houston’s water utilities and citizens.

The city of Houston and water authorities in the region have embarked on a multi-year project to construct a major expansion to the Northeast Water Purification Plant (NEWPP). This project will increase capacity from 80 MGD to 400 MGD. Using Carollo’s Blue Plan-it® Decision Support System, a digital-twin type of operation model was developed for the NEWPP to assist the engineers, managers, and operators to virtually experiment with their facility to support operational decisions (Figure 1).

Calibrated using full-scale, pilot-scale, and bench testing data, our digital twin can track flow and mass balance, estimate solids production and chemical usage, simulate truck traffic associated with chemical and solids hauling, and assess power consumption. With several mechanistic-based water treatment analytics integrated, it can be used to assess concentration-time (CT) and predict disinfection byproduct (DBP) formation for the plant’s multi-disinfectant systems, including ozone, chlorine dioxide, chlorine, and chloramine. It can simulate the impacts of chemical additions on water quality, tracking 15 corrosion and stability indices using standard algorithms similar to those used by the RTW model, Water Pro model, EPA WTP Model, etc.

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Taxonomy

• Drinking Water Treatment
• Water Treatment & Control
• Disinfection
• Water treatment
• Machine Learning
• Digital Twins
• Water, Waste Water Chemical & Treatment
• water treatment operator
• Water Quality