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Title: Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column

Authors:
 [1];  [1];  [1];  [2];  [3];  [1]
  1. Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA
  2. Pacific Northwest National Laboratory, Energy and Environment Directorate, Richland WA
  3. Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos NM
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1374663
Grant/Contract Number:
AC05-76RL01830
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Greenhouse Gases: Science and Technology
Additional Journal Information:
Journal Volume: 7; Journal Issue: 4; Related Information: CHORUS Timestamp: 2017-10-20 17:39:16; Journal ID: ISSN 2152-3878
Publisher:
Society of Chemical Industry, Wiley
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Wang, Chao, Xu, Zhijie, Lai, Canhai, Whyatt, Greg, Marcy, Peter, and Sun, Xin. Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column. United Kingdom: N. p., 2017. Web. doi:10.1002/ghg.1682.
Wang, Chao, Xu, Zhijie, Lai, Canhai, Whyatt, Greg, Marcy, Peter, & Sun, Xin. Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column. United Kingdom. doi:10.1002/ghg.1682.
Wang, Chao, Xu, Zhijie, Lai, Canhai, Whyatt, Greg, Marcy, Peter, and Sun, Xin. 2017. "Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column". United Kingdom. doi:10.1002/ghg.1682.
@article{osti_1374663,
title = {Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column},
author = {Wang, Chao and Xu, Zhijie and Lai, Canhai and Whyatt, Greg and Marcy, Peter and Sun, Xin},
abstractNote = {},
doi = {10.1002/ghg.1682},
journal = {Greenhouse Gases: Science and Technology},
number = 4,
volume = 7,
place = {United Kingdom},
year = 2017,
month = 4
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on April 27, 2018
Publisher's Accepted Manuscript

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  • A hierarchical model calibration and validation is proposed for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO2) capture is simulated and simulation results are compared to the parallel bench-scale experimental data. Two unit problems with increasing level of complexity are proposed to breakdown the complex physical/chemical processes of solvent-based CO2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e. the CO2 mass transfer across a falling ethanolaminemore » (MEA) film in absence of chemical reaction. This problem is investigated both experimentally and numerically using nitrous oxide (N2O) as a surrogate for CO2. To capture the motion of gas-liquid interface, a volume of fluid method is employed together with a one-fluid formulation to compute the mass transfer between the two phases. Bench-scale parallel experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration. Two important transport parameters, e.g. Henry’s constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as the input for the second unit problem to address the chemical adsorption of CO2 across the MEA falling film, where both mass transfer and chemical reaction are involved.« less
  • The first part of this paper (Part 1) presents a numerical model for non-reactive physical mass transfer across a wetted wall column (WWC). In Part 2, we improved the existing computational fluid dynamics (CFD) model to simulate chemical absorption occurring in a WWC as a bench-scale study of solvent-based carbon dioxide (CO2) capture. To generate data for WWC model validation, CO2 mass transfer across a monoethanolamine (MEA) solvent was first measured on a WWC experimental apparatus. The numerical model developed in this work has the ability to account for both chemical absorption and desorption of CO2 in MEA. In addition,more » the overall mass transfer coefficient predicted using traditional/empirical correlations is conducted and compared with CFD prediction results for both steady and wavy falling films. A Bayesian statistical calibration algorithm is adopted to calibrate the reaction rate constants in chemical absorption/desorption of CO2 across a falling film of MEA. The posterior distributions of the two transport properties, i.e., Henry’s constant and gas diffusivity in the non-reacting nitrous oxide (N2O)/MEA system obtained from Part 1 of this study, serves as priors for the calibration of CO2 reaction rate constants after using the N2O/CO2 analogy method. The calibrated model can be used to predict the CO2 mass transfer in a WWC for a wider range of operating conditions.« less
  • A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of theirmore » inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.« less
  • To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesianmore » calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.« less