Abstract

The commercial feasibility of the first fusion power plant generation adopting D-T plasma is strongly dependent upon the self-sustainability in terms of tritium fuelling. Within such a kind of reactor, the component selected to house the tritium breeding reactions is the breeding blanket, which is further assigned to heat power removal and radiation shielding functions. As a consequence of both its role and position, the breeding blanket is heavily exposed to both surface and volumetric heat loads and, hence, its design requires a typical multiphysics approach, from the neutronics to the thermo-mechanics. During last years, a great deal of effort has been put in the optimization of the breeding blanket design, with the aim of maximizing the tritium breeding and heat removal performances without undermining its structural integrity. In this paper, a derivative-free optimization method named “Complex method” is applied for the design optimization of the European DEMO Water-Cooled Lithium Lead breeding blanket concept. To this purpose, a potential performances-based objective function, focusing on the maximization of the tritium breeding, is defined and a multiphysics numerical model of the blanket is developed in order to solve the coupled thermo-mechanical problem, while the optimization algorithm leads the design towards a minimum optimum point compliant with the prescribed requirements. Once the optimized design is obtained, its nuclear and thermo-structural performances are assessed by means of specific neutron transport and multiphysics simulations, respectively. Finally, the structural integrity is verified by means of the application of the RCC-MRx design criteria. • A tool for First Wall optimization in water-cooled breeding blankets is developed. • The optimization is performed using the gradient-free method named “Complex method”. • An objective function aiming at tritium breeding maximization is defined. • A FE model is used to check the compliance with the thermo-structural requirements. • The optimized design is finally assessed by proper, more detailed numerical analyses.

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