A Smart Manufacturing Use Case: Furnace Temperature Balancing in Steam Methane Reforming Process via Kepler Workflows





Citation of Original Publication

Korambath, Prakashan, Jianwu Wang, Ankur Kumar, Jim Davis, Robert Graybill, Brian Schott, and Michael Baldea. “A Smart Manufacturing Use Case: Furnace Temperature Balancing in Steam Methane Reforming Process via Kepler Workflows.” Procedia Computer Science, International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA, 80 (January 1, 2016): 680–89. https://doi.org/10.1016/j.procs.2016.05.357.


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The industrial scale production of hydrogen gas through steam methane reforming (SMR) process requires an optimum furnace temperature distribution to not only maximize the hydrogen yield but also increase the longevity of the furnace infrastructure which usually operates around 1300 degree Kelvin (K). Kepler workflows are used in temperature homogenization, termed as balancing of this furnace through Reduced Order Model (ROM) based Matlab calculations using the dynamic temperature inputs from an array of infrared sensors. The outputs of the computation are used to regulate the flow rate of fuel gases which in turn optimizes the temperature distribution across the furnace. The input and output values are stored in a data Historian which is a database for real-time data and events. Computations are carried out on an OpenStack based cloud environment running Windows and Linux virtual machines. Additionally, ab initio computational fluid dynamics (CFD) calculation using Ansys Fluent software is performed to update the ROM periodically. ROM calculations complete in few minutes whereas CFD calculations usually take a few hours to complete. The Workflow uses an appropriate combination of the ROM and CFD models. The ROM only workflow currently runs every 30 minutes to process the real-time data from the furnace, while the ROM CFD workflow runs on demand. ROM only workflow can also be triggered by an operator of the furnace on demand.