Carson received her BS in Mechanical Engineering from MIT and her Ph.D. from Stanford University. Her research uses detailed process modeling, optimization, and technoeconomic assessment to design and assess desalination processes, with a focus on high salinity brine treatment for MLD/ZLD, brine valorization, and water reuse. She is interested in externalizing these tools for broader use across the water treatment industry.
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Overview
Municipal and industrial water treatment facilities face increasingly complex technology decisions for treating nontraditional waters, water reuse, and resource recovery. Current tools provide limited capability to rigorously compare alternatives, predict performance under variable conditions, or justify R&D and pilot investments. This results in conservative design decisions, costly and time-intensive piloting programs, and missed opportunities for innovation. WaterTAP is an open-source, physics-based modeling framework for designing and evaluating advanced water treatment systems. WaterTAP process models are built within an optimization framework to solve for cost-optimal design and operation. WaterTAP enables researchers and engineers to simulate complex treatment trains; screen and prioritize technologies for piloting; integrate facility data into predictive models; and quantify the value of innovation.
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Overview
Most pathways for decarbonizing the electricity sector by 2050 include substantial increases in intermittent renewable generation paired with several TWh of grid-scale energy storage. Grid scale storage includes the ability to shift or schedule large amounts of power over time and can be deployed via a diverse range of technologies, like batteries or pumped hydropower. This project aims to understand the degree to which we can use existing infrastructure as virtual storage, by scheduling the operations and consequently the power consumption of electrified industrial processes (e.g., water treatment plants, chemical manufacturing, data centers, etc.). Our group develops methods rooted in numerical optimization to design, operate, and evaluate energy flexibility strategies across a range of industrial sectors and geographic regions. By modeling these processes from the ground up, we aim to understand the cost and feasibility requirements to unlock more flexibility from existing infrastructure and strategies to design and deploy flexibility more effectively for next generation infrastructure.
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Critical minerals like lithium, cobalt, and rare earth elements are essential to the energy transition, yet current supply chains are geographically concentrated, environmentally costly, and vulnerable to market fluctuations. Our group develops techno-economic models to evaluate both conventional and emerging extraction pathways for these materials. A core focus is lithium extraction, where we compare the cost, energy intensity, and scalability of conventional evaporation-pond brine processing against direct lithium extraction (DLE) technologies for unconventional brine sources such as geothermal brines. As part of this effort, we partner with teams developing electrodialysis-based lithium extraction technologies under separate DOE-funded projects, evaluating their techno-economic performance and scale-up potential relative to conventional and other DLE approaches. We also contribute to the HERMES consortium (Hastening the Exploration & Recovery of Minerals from Earth Energy Systems), an initiative to quantify the potential value of critical minerals contained in waste resources across the United States in diverse resource and market combinations, including coal refuse, coal ash, mine tailings, acid mine drainage, and red mud. Working alongside our colleagues in the SLAC National Accelerator Laboratory and six other national labs, we model and evaluate production processes and their costs, integrating AI and data-driven methods, with the broader goal of identifying which waste-to-mineral pathways are worth pursuing at scale.
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Overview
Desalination at inland brackish groundwater treatment plants is currently limited by high costs of concentrate management and disposal. With current methods, 5-25% of the feed is disposed of as concentrate, with 98% of disposal using conventional methods (i.e. no byproduct recovery). The levelized cost of water (LCOW) for current plants in operation ranges from $0.42-1.5/m3. This project aims to assess the technical and economic feasibility of industrial ecosystems to desalinate brackish groundwater and supply existing and potential markets for clean concentrate or other bulk constituents from the brine. Specific project goals include: 1) Developing location specific byproduct revenue models using market assessments, and 2) Creating treatment train schemas in WaterTAP for treatment and valorization of brackish groundwater and establish pipe parity cost and performance targets for brackish groundwater treatment.
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Overview
This project seeks to provide a framework for selecting water resource recovery facility (WRRF) modeling platforms based on their ability to incorporate effluent limits, resource recovery, and energy-flexible operation goals. By benchmarking mechanistic (e.g., GPS-X, SUMO) and data-driven platforms, and considering the role of numerical optimization (e.g., WaterTAP), we demonstrate how platform selection affects design decisions including aeration system sizing, time-of-use electricity cost optimization, and identification of process synergies that reduce overall lifetime cost. Although established platforms excel at simulation of a given design, integrated design and operation decisions across complex treatment trains benefit from systematic design space exploration.
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