Research

                                               Multi-Scale Modeling and Optimization of Smart Water Infrastructure Systems

Funded Research Projects

Project: “Online Sensing, Multi-Scale Modeling, and Bayesian Optimization to Improve Efficiency and Resiliency of DoD Potable Water Infrastructure”
Role: PI
Source: US Navy (N3943024C2021)
Total Award: $329,115; UIC’s Amount: $329,115; SWIM Lab Share: 100%
Period: 09/16/24 – 09/15/2027

This project aims to optimize and integrate smart water infrastructure monitoring, sensing, and metering data with automated hydraulic controls to establish a system-level control framework for water utility infrastructure management and operation. This smart water infrastructure monitoring and control (SWIMC) system will be capable of: (1) Quantitatively assessing the vulnerability and resiliency of a DoD Water Distribution Networks (WDNs); (2) Quantify the lower flow limits and overall water demand requirements for maintaining water quality (WQ); (3) Optimize the placement of smart water components, including WQ sensors, chlorine boosters, and hydraulic controls such as directional flow control valves or automated flushing devices; (4) Quantify the improvement in water resiliency for the optimized WDN with different levels of smart water infrastructure implementation; (5) Quantify the impacts of low flows on WDN WQ in various water resiliency and vulnerability scenarios; and (6) Enable real-time monitoring of a WDN including leak detection and early detection of contamination episodes.

Project: “Collaborative Research: Solids and reactive transport processes in sewer systems of the future: modeling and experimental investigation”
Role: PI
Source: NSF-CBET (2134747)
Total Award: $418,277; UIC’s Amount: $208,277; SWIM Lab Share: 100%
Period: 01/01/24 – 12/31/2026

This project aims to investigate the dynamic characteristics of domestic solids discharged to sewers, the factors that affect the transport, deposition, and accumulation of these solids, and the formation and transformation of hydrogen sulfide and other key biochemical species in sewer systems. The specific objectives of this project are to 1) conduct lab and field experiments to characterize the physical aspects of gross solids transport, deposition, and transformation in sewers; 2) develop open-source software tools to model solid-liquid biochemical interactions, enable tracking the fate and transport of key biochemical species in sewer systems, and quantify and propagate different sources of uncertainty; and 3) create a computational framework for identifying potential breakpoints due to future changes in the characteristics of wastewater discharges under various decentralized water technologies, population shifts, and changes in infiltration/inflow patterns due to climate change. The successful completion of this project will bridge the fundamental knowledge gaps in solids transport and solid-liquid biochemical processes in sewer systems and will enable the identification of vulnerabilities under future uncertain long- and short-term shifts in wastewater characteristics.

Project: “Collaborative Research: Joint Control of Hydraulics and Water Quality Dynamics in Drinking Water Networks.”
Role: PI
Source: NSF-DCSD (2015603)
Total Award: $773,162; UIC’s Amount: $258,446; SWIM Lab Share: 100%
Period: 09/01/2020 – 08/31/2024

This project aims to create new methods for real-time water quality management in urban water networks by controlling hydraulic pumps, valves, and disinfectant dosing stations in response to contamination events. To this end, this research harnesses recent advances in water sensing technologies and control algorithms to enable real-time monitoring and control of hydraulics and water quality, allowing water utilities to respond rapidly to contamination events. This project puts forth a novel mathematical framework that couples the hydraulic equations governing water flow and pressure with dynamic water quality models depicting the transport and decay of disinfectant residuals, which act as a proxy for contamination event detection in drinking water distribution networks. The resulting framework faithfully describes the network operation under regular conditions and contamination events. This framework also enables the development of scalable optimization algorithms that are amenable to real-time implementation for control of pumps, valves, and disinfectant booster stations, thereby ensuring compliance with water quality standards. The algorithms are designed to deal with a variety of water system applications such as flow modulation, response and recovery from contaminant intrusion events, and reliable network-wide disinfection. The theory is evaluated on realistic water network models in addition to data from fixed and mobile sensors that collect hydraulic and water quality data from a real-life water system.

Project: “Selective Electrocatalytic Destruction of PFAS using a Reactive Electrochemical Membrane System.”
Role: Co-PI
Source: National Alliance for Water Innovation – US Department of Energy
Total Award: $ 1,968,000 (with cost share); UIC’s Amount: $1,063,288; SWIM Lab Share: 33%
Period: 09/01/22 – 08/31/2025

The proposed research will investigate the selective removal and reductive electrocatalytic destruction of poly- and per-fluorinated alkyl substances (PFAS) as a desalination concentrate management strategy, with a specific focus on the treatment of reverse osmosis (RO) concentrates from industrial and municipal wastewaters. We have assembled a strong team to develop and optimize efficient electrocatalysts for the reductive defluorination of PFAS into benign byproducts. To that end, electrocatalysts will be doped on selective PFAS adsorbents and deposited on a reactive electrochemical membrane (REM) support. These materials will be thoroughly characterized and refined through computationally guided synthesis. The synthesized materials will be screened at the bench-scale, and the most promising materials will be extensively studied for their reactivity, selectivity, and longevity in real and synthetic RO concentrates.

Project: “Collaborative Research: Environmental Sensing of Per and Polyfluoroalkyl Substances in Water Utilizing a Microelectrode Sensor Array Platform and Machine Learning Enabled Detection”
Role: Co-PI
Source: NSF-CBET (2149235)
Total Award: $465,181; UIC’s Amount: $445,181; SWIM Lab Share: 33%
Period: 09/01/22 – 08/31/2025

This project aims to create a bottom-up framework for the development of mobile, low-cost PFAS sensing platforms that can be used in-situ and at the point-of-use to monitor PFAS contamination in water. The proposed framework will be demonstrated through the development of a functionalized microelectrode sensor array (MESA) platform, coupled with machine learning algorithms, for the detection and quantification of a mixture of PFAS with a range of physical properties in diverse water matrices. The specific research objectives of this project are to: (1) characterize the fundamental adsorption/desorption mechanisms of PFAS on sorbent materials using an electrochemical quartz crystal microbalance experimental setup; (2) utilize computational density functional theory calculations to reveal the specific surface interactions that control PFAS adsorption/desorption on different sorbent materials; (3) integrate the experimental-computational results to guide the selection of selective, reversible adsorbents for various PFAS; and (4) fabricate and test a machine-learning enabled MESA platform for PFAS detection. The successful completion of this project has the potential for transformative impact through the development of a sensor for the selective detection of individual compounds within a PFAS mixture with detection limits in the low ng/L concentration range and reliable performance in varying source water matrices.

Project: “RET Site: Computational Modeling and Simulation for Science, Technology, Engineering, and Mathematics Education”
Role: Senior Personnel
Source: NSF-EEC (2302171)
Total Award: $600,000; UIC’s Amount: $600,000; SWIM Lab Share: 10%
Period: 10/01/23 – 09/30/2026

This RET project brings together a multidisciplinary team from the Departments of Chemical Engineering, Civil and Environmental Engineering, Mechanical and Industrial Engineering, and Chemistry at the University of Illinois Chicago (UIC) to provide high school STEM teachers with the opportunity to learn about Computational Modeling and Software (CMS), focusing on applications in the fields of (1) Nanotechnology, (2) Data-driven modeling and machine-learning, (3) Drug design and delivery, and (4) Biomechanics. Partnering with minority-serving public and private high schools in Chicago, ten recruited teachers will be selected based on application materials and immersed in cutting-edge research activities to enhance their perspectives on CMS. The teachers will participate in a six-week summer program and become part of a research community that includes faculty mentors, education advisors, industry professionals, and graduate and undergraduate students. Through professional development activities, the teachers will work with the project team to devise inquiry-based and Next Generation of Science Standards-aligned lesson plans and curricular modules to be integrated into the classroom in the following academic year. Lesson plans and learning modules will be disseminated through the UIC and Chicago Public Schools websites, annual conferences, and the NSF repository.