Development of Hybrid Digital Twins for Predictive Nutrient Control

This project developed, implemented, and studied how live digital twins of nutrient removal water resource recovery facilities (WRRFs), which included machine learning (ML), could be used to benefit ongoing operations. In the three full scale pilots completed, digital twins were not only able to benefit the targeted goals of these facilities, but provided significant ancillary benefits that address many of the additional challenges that operators, engineers, and managers face as they balance regulatory, environmental, financial, and labor force concerns. Research partner: Alexandria Renew Enterprises. Published in 2024.