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Project #5121

Development of Hybrid Digital Twins for Predictive Nutrient Control

$666,135
Completed
Principal Investigator
Bruce
Johnson
Research Manager
Harry Zhang, PhD, PE
Contractor
Jacobs
Intelligent Water Systems
Big Data
Nutrients
Sensors
Biological Nutrient Removal (BNR)
Final Report

Abstract

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.