TY - GEN
T1 - RELIABILITY-BASED OPTIMIZATION OF OFFSHORE SALT CAVERNS FOR CO2 ABATEMENT
AU - Zheng, Zhuoyuan
AU - Xu, Yanwen
AU - Hamdan, Bayan
AU - Kohtz, Sara
AU - Costa, Pedro V.M.
AU - Costa, Alvaro M.
AU - Morais, Carlos H.B.
AU - Wang, Pingfeng
N1 - This research is partially supported by the National Science Foundation (NSF) the Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS) with cooperative agreement EEC-1449548, and the Alfred P. Sloan Foundation through the Energy and Environmental Sensors program with grant # G-2020-12455.
PY - 2022
Y1 - 2022
N2 - In recent years, projects have been proposed to utilize salt caverns as a storage method for supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively reduce the anthropogenic greenhouse gases (GHG) concentration. Careful and rational design of the salt cavern are required to guarantee the structural stability and reliability of the cavern when in service. In this study, physics-based FE models were first developed to simulate the salt cavern construction process and predict the creep deformation of the cavern wall during s-CO2 storage. In addition, Gaussian process (GP) based surrogate models were constructed from FE simulation results to estimate the properties of salt caverns with cheaper calculations. Then, to obtain a reliable and robust design, an RBDO framework was employed with the assistance of an adaptive fidelity enhancement technique to scan through the high-dimensional design space, which provides a swift and efficient search for the optimal conditions while considering the uncertainties in the salt cavern construction process. This research is one of the first to account for uncertainties within the salt cavern design process, and the results show that uncertainties of variables can strongly affect the system reliability and the volume of the salt cavern.
AB - In recent years, projects have been proposed to utilize salt caverns as a storage method for supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively reduce the anthropogenic greenhouse gases (GHG) concentration. Careful and rational design of the salt cavern are required to guarantee the structural stability and reliability of the cavern when in service. In this study, physics-based FE models were first developed to simulate the salt cavern construction process and predict the creep deformation of the cavern wall during s-CO2 storage. In addition, Gaussian process (GP) based surrogate models were constructed from FE simulation results to estimate the properties of salt caverns with cheaper calculations. Then, to obtain a reliable and robust design, an RBDO framework was employed with the assistance of an adaptive fidelity enhancement technique to scan through the high-dimensional design space, which provides a swift and efficient search for the optimal conditions while considering the uncertainties in the salt cavern construction process. This research is one of the first to account for uncertainties within the salt cavern design process, and the results show that uncertainties of variables can strongly affect the system reliability and the volume of the salt cavern.
KW - Carbon capture and storage
KW - Finite element modeling
KW - Gaussian process
KW - Reliability-based design optimization
KW - Salt cavern
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U2 - 10.1115/DETC2022-90496
DO - 10.1115/DETC2022-90496
M3 - Conference contribution
AN - SCOPUS:85142505332
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 48th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Y2 - 14 August 2022 through 17 August 2022
ER -