UCLA

Hydrogen is proposed by many to be the fuel of the future as it is the key ingredient in a transition from a fossil fuel-based economy toward a zero carbon emission and sustainable energy economy. Hydrogen can serve as an efficient energy carrier for hydrogen-based technologies (e.g., fuel cells and hydrogen internal combustion engine) and lead to substantial reduction of greenhouse gas emissions and great environmental benefits. Hydrogen can be produced by a variety of technologies (e.g., steam methane reforming (SMR), coal gasification, biomass gasification, electrolysis, partial oxidation, solar thermal cracking) from fossil (e.g., natural gas), non-fossil (e.g., biogas) and non-carbon (e.g., water) sources, which highlights the great potential and flexibility of a hydrogen-based economy. Additionally, hydrogen is a key feedstock for the petroleum refining and fine chemical manufacturing industries. With current state-of-the-art technology, hydrogen is produced almost exclusively from fossil fuels by SMR. At SMR-based hydrogen plants, the reformers are the most expensive equipment in terms of the maintenance and operating costs, and thus, even a small improvement in the reformer thermal efficiency to lower operating costs of the reformer without compromising the expected service life of the reformer is expected to allow the plants to achieve a significant profit.

Motivated by these considerations, a systematic framework for creating and simulating a computational fluid dynamics (CFD) model for an industrial-scale reformer at an SMR-based hydrogen plant and, subsequently, a framework for designing and evaluating a real-time furnace balancing scheme are developed in this dissertation. Specifically, a CFD model for an industrial-scale reformer is created in ANSYS Fluent, which is used to improve our understanding of the physiochemical processes in the tube side and the furnace side of the reformer as well as their thermal interactions during the catalytic conversion of methane. Then, a furnace balancing scheme is developed to optimize the reformer input at the nominal total furnace-side feed (FSF) flow rate that minimizes the inherent variability in the outer tube wall temperature (OTWT) distributions along the reforming tube length. Subsequently, a statistical-based model identification is developed to create a computationally efficient and robust model for the OTWT distribution as a function of the FSF distribution, total FSF flow rate and interactions among neighboring reforming tubes so that the optimized reformer input can be identified in real-time. Finally, a real-time furnace-balancing scheme is developed to optimize the reformer input such that the reformer thermal efficiency is maximized without compromising the expected service life of the reformer.