Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Project: Research project

Project Details


The work to be performed at Northwestern University (NU) is divided into two sections as part of application (task) 1: 1) Data analytics and development of data-driven control concept for high-rate CS systems; and 2) molecular microbial population monitoring. All work will be performed in close collaboration with DC Water, where pilot- and full-scale testing will be performed, and with Dr. Kris Villez at ONL for support of data-driven control concepts. 1) Data analytics and development of data-driven control setup In coordination with DC Water, NU will compile data for pilot-scale high rate CS pilot scenario evaluations with different MLSS setpoints, including COD, N and P mass balances and settling behavior. Allied datasets will be collected based on historical data collection from full-scale CS and non-CS operation. In coordination with ONL, the datasets will be employed to build a data driven model of settleability, effluent quality, and carbon/ nutrient redirection. The model will then be used to develop a data-driven control system that will be implemented and tested on the pilot-scale high rate CS system. 2) Molecular microbial population monitoring NU will use a molecular fingerprinting approach to evaluate predictability of settling behavior based on amplicon sequencing. Biomass samples from pilot- and full-scale systems will be subject to 16S rRNA gene amplicon sequencing using Illumina MiSeq, and in select samples with alternate rapid sequencing technologies. Molecular signatures will be characterized as a fingerprint of settling regime and potential future signal for settling behavior detection.
Effective start/end date10/1/211/31/24


  • Water Research Foundation (DE-EE0009508//5143)
  • Department of Energy (DE-EE0009508//5143)


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