(756a) Enhanced Furnace Balancing Scheme Via an Integrated Computational Fluid Dynamics/Data-Based Optimization Approach
AIChE Annual Meeting
Thursday, November 2, 2017 - 3:15pm to 3:34pm
Motivated by this, the present work focuses on developing an advanced furnace balancing scheme via an integrated computational fluid dynamics/data-based optimization approach that optimizes not only the distribution of burner mass flow rates but also the total mass flow rate through the burners such that the degree of temperature nonuniformity inside the reformer is minimized, while the maximum outer reforming tube wall temperature is kept strictly below the design temperature of the wall material, and the hydrogen production rate is maximized without reducing the reformer service life. The furnace balancing scheme employs computational fluid dynamics modeling to generate data that is used in identifying a data-driven model for the optimization-based furnace balancing scheme and for validating the data-driven model. The furnace balancing optimization problem simultaneously solves for the optimal total mass flow rate through the burners and the individual mass flow rates through each burner. The robustness of the furnace balancing scheme to disturbances is compared with the robustness of a furnace balancing scheme developed in  that assumes a constant total mass flow rate. The data-driven model development follows statistical principles to allow it to make reasonable out-of-sample predictions of the OTWT distribution for various mass flow rate distributions and also for various total mass flow rates. The ability to adjust the total mass flow rate for the advanced furnace balancing scheme is of special interest for the hydrogen manufacturing industry as it can potentially lead to substantial savings in the re-tubing cost of the reformer.
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