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Title: Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.
Authors:
ORCiD logo [1] ;  [2] ; ORCiD logo [3]
  1. National Energy Technology Lab. (NETL), Morgantown, WV (United States). Science & Technology Strategic Plans & Programs
  2. National Energy Technology Lab. (NETL), Morgantown, WV (United States). Research & Innovation Center; West Virginia Univ., Morgantown, WV (United States). Mechanical and Aerospace Engineering
  3. National Energy Technology Lab. (NETL), Morgantown, WV (United States). Research & Innovation Center
Publication Date:
Report Number(s):
NETL-PUB-21134
Journal ID: ISSN 0001-1541
Type:
Accepted Manuscript
Journal Name:
AIChE Journal
Additional Journal Information:
Journal Volume: 63; Journal Issue: 12; Journal ID: ISSN 0001-1541
Publisher:
American Institute of Chemical Engineers
Research Org:
National Energy Technology Lab. (NETL), Pittsburgh, PA, and Morgantown, WV (United States)
Sponsoring Org:
USDOE Office of Fossil Energy (FE)
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; 22 GENERAL STUDIES OF NUCLEAR REACTORS; two‐fluid model; multiphase computational fluid dynamics; uncertainty quantification; discretization error; time‐averaging error
OSTI Identifier:
1440343

Syamlal, Madhava, Celik, Ismail B., and Benyahia, Sofiane. Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions. United States: N. p., Web. doi:10.1002/aic.15868.
Syamlal, Madhava, Celik, Ismail B., & Benyahia, Sofiane. Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions. United States. doi:10.1002/aic.15868.
Syamlal, Madhava, Celik, Ismail B., and Benyahia, Sofiane. 2017. "Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions". United States. doi:10.1002/aic.15868. https://www.osti.gov/servlets/purl/1440343.
@article{osti_1440343,
title = {Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions},
author = {Syamlal, Madhava and Celik, Ismail B. and Benyahia, Sofiane},
abstractNote = {The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.},
doi = {10.1002/aic.15868},
journal = {AIChE Journal},
number = 12,
volume = 63,
place = {United States},
year = {2017},
month = {7}
}