Research Interests: process modeling, optimization, techno-economic analysis, lifecycle assessment, surrogate modeling, brine management, resource recovery, circular economy, water treatment
Software Skills: Python, MATLAB, R, Aspen Plus, Aspen Custom Modeler, CHEMCAD, AVEVA Process simulation
Abstract: Advancing sustainable and cost-effective water treatment requires integrating accurate modeling, optimization, and techno-economic analysis to inform process design and decision-making. This research focuses on developing computational frameworks that combine detailed physicochemical modeling with process systems engineering tools to assess and improve desalination and brine management strategies.
A key area of investigation involves evaluating the trade-offs of simplifying water property models in desalination processes. Due to the complexity of aqueous chemistry, detailed models can pose computational challenges, motivating the use of simplified sodium chloride-based models. By systematically comparing these models for reverse osmosis and mechanical vapor compression, this work quantifies the impacts of modeling assumptions affect process optimization outcomes, guiding model selection to balance accuracy with computational efficiency.
To address persistent contaminant challenges, such as boron removal in seawater desalination, this research integrates chemical equilibrium modeling, surrogate modeling, and process simulation to enable techno-economic optimization of treatment strategies. This approach facilitates the development of cost benchmarks for existing two-pass reverse osmosis with pH swing systems and establishes economic targets for emerging technologies.
Additionally, ongoing work focuses on developing superstructure-based optimization frameworks for brine valorization in brackish water desalination. By evaluating treatment train configurations for resource recovery, including sodium chloride, acid-base generation, and calcium-based products, this research seeks to reduce treatment costs while promoting circular economy goals.
Overall, this work demonstrates how integrating physicochemical property modeling with optimization and techno-economic analysis can inform the design of sustainable, efficient, and economically viable water treatment and resource recovery systems.