Abstract
Mathematical modeling and optimization form the backbone of system-level analysis for emerging energy processes, enabling quantification of performance trade-offs and guiding design decisions. My PhD work develops integrated equation-oriented and data-driven frameworks that span reactor-scale phenomena through plant-wide techno-economic analysis. This abstract highlights three pillars of my research: steady-state modeling and optimization of water–gas shift membrane reactors (WGS-MR); techno-economic optimization of biogas-fed ammonia synthesis; and reduced-order kinetic (ROK) modeling with catalyst-decay surrogates for olefin oligomerization.
Water–Gas Shift Membrane Reactor Modeling & Optimization
An equation-oriented, steady-state model of the WGS-MR unit was implemented in Python to solve coupled reaction and permeation balances under nonlinear reaction kinetics and membrane transport constraints. I formulated a nonlinear program (NLP) to minimize the levelized cost of hydrogen (LCOH) by optimally tuning reactor temperature and gas hourly space velocity, while enforcing CO conversion and H₂ recovery targets. Furthermore, I conducted targeted technoeconomic analyses (TEAs) to quantify the benefits of process intensification in biomass-based H2 production using WGS-MR, resulting in a 9.6% decrease in LCOH compared to the baseline with conventional WGS reactors and pressure swing adsorption.
Ammonia Synthesis Techno-Economic Optimization
Five biogas-based ammonia production routes—steam methane reforming (SMR), autothermal reforming (ATR), catalytic partial oxidation (CPOx), methane pyrolysis (MP), and chemical-looping combustion (CLC)—were built as steady-state flowsheets in Aspen Plus v14. Each flowsheet integrates validated reformer kinetics, biogas upgrading units, and the Haber–Bosch loop. These models were used to furnish a detailed comparative analysis, including TEA and life cycle assessment. I found that MP with carbon-black valorization yields the lowest MASP and the most significant carbon avoidance per dollar, offering a clear techno-economic ranking for biogas-to-ammonia pathways. I also quantified the impact of geospatial uncertainties on biogas availability, as well as the price and carbon footprint of the electric grid, on the NH3 production systems across the USA.
Oligomerization Reaction Kinetics & Catalyst-Decay Modeling
To accelerate catalyst design for shale-gas-derived olefin oligomerization, I am leveraging reduced-order kinetic (ROK) models developed within our group to support process-scale optimization of shale gas upgrading into high-value fuels and chemicals. Following the successful validation of the ROK model with pilot-plant data from our experimental collaborators, I incorporated catalyst decay kinetics through data-driven models to reflect the true behavior of the reactor system. A comparative study of ROK variants (including models M4 and M5) identified the surrogate formulation that minimizes mean-squared-logarithmic-error against experimental conversion and product-distribution datasets, validating the approach for rapid integration into flowsheet-level studies.
Key Results
Implications for Industry
These frameworks offer industry stakeholders quantitative tools for evaluating technology, intensifying processes, and developing catalysts. The WGS-MR model guides membrane-based hydrogen intensification strategies, the ammonia optimization delivers location-agnostic techno-economic benchmarks for biogas utilization, and the ROK-PINN surrogates enable rapid screening of catalyst materials and deactivation modes. Collectively, this research accelerates the deployment of sustainable energy processes by offering actionable insights grounded in mathematical rigor and scalable computational workflows.