A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field. (4th October 2017)

• Record Type: Journal Article
• Authors: Kumar, Ankur; Baldea, Michael; Edgar, Thomas F.
• Is Part Of: Computers & chemical engineering. Volume 105(2017)
• Page Start: 224
• Page End: 236
• Publication Date: 2017-10-04
• Subjects: Steam-methane reformer -- Furnace balancing -- Process intensification -- Smart manufacturing -- Process optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2017.01.002
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract : Highlights: Physics-based model enables study of non-uniform furnace temperature distribution. Novel empirical modeling scheme used to fit the real-plant temperature distribution. Reasonably low computational time makes the model suitable for online optimization. Optimization scheme uses physics-based model for furnace operation intensification. Abstract: In an industrial hydrogen production facility, steam-methane reforming reactions take place inside hundreds of catalyst-filled tubes placed in a large scale, high temperature furnace. Process efficiency depends strongly on the wall temperature distribution of the ensemble of reformer tubes; a narrower distribution has a process intensification effect, by providing similar processing experience to every feedstock molecule. Such process intensification efforts require a furnace model that can predict the temperature distribution as a function of operating conditions. Currently available furnace modeling solutions are either computationally intensive, making them unsuitable for (online) optimization calculations, or empirical, having limited accuracy when wide changes in operating conditions are required. In this work, a physics-based furnace model is presented that overcomes these limitations. Empirical perturbations in a Hottel zone radiation model are proposed to capture the spatially non-symmetrical temperature distribution. The low computational time makes the model suitable for operational intensification based on reduction of temperature distribution non-uniformity.