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Title: A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field

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. Here 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.

Authors:
 [1];  [1];  [1]
+ Show Author Affiliations
  1. University of Texas, Austin, TX (United States)
Publication Date:
Research Org.:
Univ. of Texas, Austin, TX (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1538170
Alternate Identifier(s):
OSTI ID: 1550652
Grant/Contract Number:  
EE0005763; EE0005763/00011
Resource Type:
Accepted Manuscript
Journal Name:
Computers and Chemical Engineering
Additional Journal Information:
Journal Volume: 105; Journal Issue: C; Journal ID: ISSN 0098-1354
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; steam-methane reformer; furnace balancing; process intensification; smart manufacturing; process optimization

Citation Formats

Kumar, Ankur, Baldea, Michael, and Edgar, Thomas F. A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field. United States: N. p., 2017. Web. doi:10.1016/j.compchemeng.2017.01.002.
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Kumar, Ankur, Baldea, Michael, & Edgar, Thomas F. A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field. United States. https://doi.org/10.1016/j.compchemeng.2017.01.002
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Kumar, Ankur, Baldea, Michael, and Edgar, Thomas F. Sat . "A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field". United States. https://doi.org/10.1016/j.compchemeng.2017.01.002. https://www.osti.gov/servlets/purl/1538170.
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@article{osti_1538170,
title = {A physics-based model for industrial steam-methane reformer optimization with non-uniform temperature field},
author = {Kumar, Ankur and Baldea, Michael and Edgar, Thomas F.},
abstractNote = {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. Here 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.},
doi = {10.1016/j.compchemeng.2017.01.002},
journal = {Computers and Chemical Engineering},
number = C,
volume = 105,
place = {United States},
year = {Sat Jan 07 00:00:00 EST 2017},
month = {Sat Jan 07 00:00:00 EST 2017}
}
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https://doi.org/10.1016/j.compchemeng.2017.01.002
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