Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

A Digital Twin built around Activated Sludge Model No. 1 was deployed at a full-scale water resource recovery facility. Its design included a waste rate recommender system based on automatic scenario analyses, where influent loads and waste rates are varied to determine their impact on nitrification. At the same frequency as these scenario analyses, scheduled auto-calibrations allow for nitrifier maximum specific growth rate (<i>μ</i><sub>max-NITO</sub>) soft sensing, the only kinetic parameter shown to require adjustment if the objective is aeration tank effluent ammonia forecasting accuracy. By integrating temperature forecasting over the next three sludge ages, this Digital Twin approach creates opportunities for advancing waste rate decisions in anticipation of seasonal temperature changes, optimizing ammonia control authority under varying influent loads, and furnishing valuable insights for future capital projects requiring nitrifier kinetic understanding and modelling.

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Publication Details

Journal
Water Science & Technology
Published
2025-07-18
DOI
https://doi.org/10.2166/wst.2025.106
Citations
1
Primary Topic
Wastewater Treatment and Nitrogen Removal
Type
article
Field-Weighted Citation Impact
0.50

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article

Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

Charles B. Bott, Peter A. Vanrolleghem, Jeffrey Sparks
1 citations
Water Science & Technology
Wastewater Treatment and Nitrogen Removal
0.50
article

Design considerations for a Digital Twin built to improve nitrification performance at a water resource recovery facility

Charles B. Bott, Peter A. Vanrolleghem, Jeffrey Sparks
article en
1 citations

Abstract

A Digital Twin built around Activated Sludge Model No. 1 was deployed at a full-scale water resource recovery facility. Its design included a waste rate recommender system based on automatic scenario analyses, where influent loads and waste rates are varied to determine their impact on nitrification. At the same frequency as these scenario analyses, scheduled auto-calibrations allow for nitrifier maximum specific growth rate (<i>μ</i><sub>max-NITO</sub>) soft sensing, the only kinetic parameter shown to require adjustment if the objective is aeration tank effluent ammonia forecasting accuracy. By integrating temperature forecasting over the next three sludge ages, this Digital Twin approach creates opportunities for advancing waste rate decisions in anticipation of seasonal temperature changes, optimizing ammonia control authority under varying influent loads, and furnishing valuable insights for future capital projects requiring nitrifier kinetic understanding and modelling.

Water Science & TechnologyVol. 92(3)
Hampton Roads Sanitation District (US), Université Laval (CA)
Office of Energy Efficiency and Renewable Energy
Clean water and sanitation
Openalex Percentile: Top 37%
Wastewater Treatment and Nitrogen Removal
0.50
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