451526 CCSI – Accelerating Carbon Capture through Modeling

Monday, April 11, 2016: 1:55 PM
339B (Hilton Americas - Houston)
Andrew Lee1, David C. Miller2, Joel D. Kress3, David S. Mebane4, Xin Sun5, Curtis B Storlie3, Sankaran Sundaresan6, Debangsu Bhattacharyya7, Nikolaos V. Sahinidis8, John C. Eslick2, Charles Tong9 and Deb Agarwal10, (1)Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, (2)National Energy Technology Laboratory, Pittsburgh, PA, (3)Los Alamos National Laboratory, Los Alamos, NM, (4)National Energy Technology Laboratory, Morgantown, WV, (5)Pacific Northwest National Laboratory, Richland, WA, (6)Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, (7)Department of Chemical Engineering, West Virginia University, Morgantown, WV, (8)Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, (9)Lawrence Livermore National Laboratory, (10)Lawrence Berkeley National Laboratory, Berkeley, CA

The Carbon Capture Simulation Initiative (CCSI) was established by the U.S. Department of Energy in 2011 as a five year project with the goal of accelerating the adoption of carbon capture technologies by the power industry. Involving a collaboration between national laboratories, universities and industry, CCSI developed a modeling toolset designed to assist industry in developing new carbon technologies and scaling up to commercial application faster. The toolset allows users to model their system at all scales of the development process, from laboratory and bench scale through to full scale commercial deployment. Another key aspect of the toolset is the incorporation of uncertainty quantification at all scales, allowing users to understand and develop strategies to minimize the uncertainty in their designs at all stages of development. Commercialization of the CCSI toolset is currently underway, and a number of large scale demonstrations of the toolset are underway in collaboration with industry partners.

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See more of this Session: Smart Manufacturing: Advances in Modeling and Sensors
See more of this Group/Topical: Topical 3: Innovative Manufacturing