TY - JOUR
T1 - Carbon capture simulation initiative
T2 - A case study in multiscale modeling and new challenges
AU - Miller, David C.
AU - Syamlal, Madhava
AU - Mebane, David S.
AU - Storlie, Curt
AU - Bhattacharyya, Debangsu
AU - Sahinidis, Nikolaos V.
AU - Agarwal, Deb
AU - Tong, Charles
AU - Zitney, Stephen E.
AU - Sarkar, Avik
AU - Sun, Xin
AU - Sundaresan, Sankaran
AU - Ryan, Emily
AU - Engel, Dave
AU - Dale, Crystal
PY - 2014/6
Y1 - 2014/6
N2 - Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-Analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.
AB - Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-Analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.
KW - Computational fluid dynamics
KW - Optimization
KW - Process control
KW - Process synthesis
KW - Risk analysis
KW - Uncertainty quantification
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U2 - 10.1146/annurev-chembioeng-060713-040321
DO - 10.1146/annurev-chembioeng-060713-040321
M3 - Article
C2 - 24797817
AN - SCOPUS:84902474546
SN - 1947-5438
VL - 5
SP - 301
EP - 323
JO - Annual Review of Chemical and Biomolecular Engineering
JF - Annual Review of Chemical and Biomolecular Engineering
ER -