Url https://www.cimne.com/sgp/rtd/Project.aspx?id=925
Acronym AMBBOS
Project title Advanced computational Mathematics for Breeding Blanket Optimal deSign
Reference PID2021-123611OB-I00
Principal investigator Ricardo Javier PRINCIPE RUBIO - principe@cimne.upc.edu
Francesc VERDUGO ROJANO - fverdugo@cimne.upc.edu
Start date 01/09/2022 End date 31/08/2025
Coordinator CIMNE
Consortium members
Program P.E. para Impulsar la Investigación Científico-Técnica y su Transferencia Call Proyectos Generación de Conocimiento 2021
Subprogram Subprograma Estatal de Generación de Conocimiento Category Nacional
Funding body(ies) MICINN Grant 175.450,00 €
Abstract We propose new mathematical and computational methods to assist in the design of breeding blankets, a critical technology to make nuclear fusion power plants a reality. Modern concepts of fusion reactors like ITER fuse deuterium and tritium, two hydrogen isotopes, producing helium, free neutrons, and large amounts of heat that can be converted into electricity. While deuterium can be obtained from sea water at the required quantities, tritium is radioactive and extremely scarce in nature. The key role of the breeding blanket is to regenerate the tritium burnt in the plasma to ensure a self-sustained fusion reaction, which would be otherwise impossible due to a limited tritium supply. The design of breading blankets is not an obvious task. A flow of molten led-lithium (Pb-Li) alloy circulates within the blanket cavities in the presence of a strong magnetic field used to confine the plasma in the fusion reactor. This induces a number of magneto hydro dynamics (MHD) effects in the flowing molten metal that need to be taken into account in the blanket design. The characterization of MHD flows via experiments is extremely expensive and there is a tremendous interest in predictive numerical simulations able to substitute experiments. However, current simulation codes are not mature enough to deal with MHD flows at the requested regimes due to a number of open mathematical and computational challenges. Current simulation tools cannot properly simulate MHD flows in the presence of strong magnetic fields, they are not able to properly capture complex blanket geometries, and shape optimization methods are lacking in this context. The main goal of the project is to address these limitations in order to increase the capacity of simulation-driven design in this area. To this end, we propose a new set of mathematical and computational tools for the approximation of the MHD equations, the partial differential equations (PDEs) governing MHD flows. We plan to develop fully monolithic solution schemes able to deal with the strongly-coupled problems associated with strong magnetic fields, embedded finite element methods to facilitate the discretization of complex blanket geometries, and new shape and optimization methods to optimize critical outputs of the MHD flow such as the pressure drop. With the resulting tools, we plan to simulate and analyze real-world breeding blanket concepts and to find optimal designs. This will require the multidisciplinary collaboration with experts on the analysis of breeding blanket concepts and also efficient implementations in parallel scientific software in order leverage the power of modern supercomputers to simulate complex problems. The resulting codes will be released as free and open-source software to facilitate their exploitation by fusion agencies like CIEMAT. By addressing the project goals, we will contribute to the development of nuclear fusion as a large-scale, sustainable, and carbon-free energy source, which is urgently needed in the current context of climate crisis and growing energy demand. In this regard, the project addresses the firth thematic priority “clima, energia y movilidad” of the Spanish research plan "Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023".
Ayuda PID2021-123611OB-I00 del proyecto financiado por MCIN/AEI/10.13039/501100011033/ y por "FEDER: Una manera de hacer Europa"